Proceedingsof the Tenth InternationalConference on
ALORIMETRY IN PARTICLE PHYSICS
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Proceedings of the Tenth International Conference on
ALORIMETRY IN PARTICLE
PHYSI
Pasadena, California, USA
25 - 29 March 2002
Editor
Ren=YuanZhu California Institute of Technology, USA
we World Scientific b
New Jersey London Singapore Hong Kong
Published by World Scientific Publishing Co. Re. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: Suite 202,1060 Main Street, River Edge, NJ 07661 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE
British Library Cataloguing-in-PublicationData A catalogue record for this book is available from the British Library.
CALORIMETRY IN PARTICLE PHYSICS Proceedings of the Tenth International Conference Copyright 0 2002 by World Scientific Publishing Co. Re. Ltd. All rights reserved. This book, or parts thereof; may not be reproduced in anyform or by any means, electronic or mechanical, includingphotocopying, recording or any informationstorage and retrieval system now known or to be invented, without wrinen permissionfrom the Publisher.
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ISBN 981-238-157-0
This book is printed on acid-free paper.
Printed in Singapore by Uto-Print
International Advisory Committee G. Bellettini J. Colas A. Ereditato F. L. Fabbri H. A. Gordon D. Green P. Jenni T. Kobayashi A. Maio A. Menzione H. Oberlack A. Para K. Pretzl J. Rutherfoord R. Wigmans R. Yoshida R-Y. Zhu
INFN /Pisa LAPP / Annecy INFN/Napoli INFN/Frascati BNL/Brookhaven FNAL /Bat avia CERN/Geneva ICEPP/Tokyo FCUL & LIP/Lisbon INFN/Pisa MPI/Munich FNAL/Batavia Bern U/Bern U. Arizona/Tucson Texas Tech/Lubbock ANL / Ar gonne Caltech/ Pasadena
Local Organization Committee J. Adams B. Barish B. Choudhary M. Gataullin D. Hitlin H. Newman F. Porter L. Xia L. Zhang R-Y. Zhu
MSFC/NASA Caltech Caltech Caltech Caltech Caltech Caltech Caltech Caltech Caltech
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Artistry Liyuan Zhang
Caltech
Computing Support Juan Barayoga Frank Porter
Caltech Caltech
Conference Web Lei Xia Kejun Zhu
Caltech Caltech
Logistics Brajes h Choudhar y Marat Gataullin
Caltech Caltech
Photography Bob Paz Qing Wei Liyuan Zhang
Caltech Caltech Caltech
Scientific Secretariat Marat Gataullin Lei Xia
Caltech Caltech
Secretariat Debbie Kingston Virginia Licon Marc Rincon Betty Smith Meiske Van der Eb
Caltech Caltech Caltech Caltech Caltech
Special thanks to the following sponsors: Division of Physics, Mathematics and Astronomy, Caltech Hamamatsu Photonics K.K. Kuraray Chemical Co. Shanghai Institute of Ceramics, Chinese Academy of Sciences
PREFACE The “loth International Conference on Calorimetry in Particle Physics’’ (Calor2002) was held from March 25th to 2gth, 2002, at the Beckman Institute Auditorium in California Institute of Technology (Caltech) and at the elegant Huntington Library, Pasadena, California, USA. The nine previous International Conferences on Calorimetry in High Energy Physics were held in Annecy (2000), Lisbon (1999), Tucson (1997), Frascati (1996), Brookhaven (1994), Elba (1993), Corpus Christi (1992), Capri (1991) and Fermilab (1990). Starting from this edition, the name of this series conference is changed to engage broad participants in particle physics community. The Calor2002 scientific program consists of three parts: 6 introductory talks, 11 sessions and 3 perspective talks. The conference is featured in all presentations given in plenary sessions, which provides an excellent opportunity for young physicists to be introduced into the community. It is also the first time in this series of conference a session is dedicated to the “Calorimetry in astrophysics”. The conference was opened by T. Tombrello, Division Chair of Physics, Mathematics and Astronomy, and D. Hitlin, Director of Caltech High Energy Physics. The program started with the introductory session chaired by R.Y. Zhu and A. Ereditado. The presentations in this session, by K. Pretzl (history), D. Fournier (LHC), S. Swordy (astrophysics), W. Wisniewski (super B factory), R. Frey (linear collider) and V. Morgunov (energy flow), covered historical, current and new trends of calorimetry development. The conference also saw a lively discussion on the issue of the “energy flow”. The 11 sessions were organized around various calorimetry techniques and applications by distinguished conveners. The calorimetry in astrophysics session, convened by T. Parnell, covered a broad range of calorimetry technologies implemented in astrophysics experiments: AMANDA, AMS, ATIC, BLAZARS, CREAM, EUSO, GLAST, OWL, PAMELA, P A 0 and VERITAS. In the crystal calorimetry session, convened by W. Wisniewski, calorimeters in BaBar, BELLE, CMS, COSY and PRIMEX were presented. The medical application session, convened by C. Woody, covered PET detector and simulation. W. Moses’s enlightening perspective talk comparing calorimetry with PET was given in this session. In the silicon calorimetry session, convened by D. Strom, experiences from OPAL and ZEUS as well as on-going design studies by linear collider communities in Europe and US were presented. The simulation session, convened by C. Seez, covered physics studies and detailed calorimeter simulations by ATLAS, CDF and CMS, where implementation of
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the “energy flow” was discussed in details. In the calibration session, convened by M. Gataullin, a broad range of calibration and monitoring techniques implemented in AMANDA, BELLE, CDF, CMS, D 0 , KLOE, MINOS, PHENIX, PRIMEX, SNO and ZEUS was presented. The Cerenkov calorimetry session, convened by S. White, covered calorimetry in CMS and RICE, where an interesting new idea of radio Cerenkov detection was discussed. In the scintillation calorimetry session, convened by M. Cavalli-Sforza,calorimeters from ATLAS, Borexino, CDF, CMS MINOS and ZEUS as well as on-going design studies for a TESLA detector were presented. The electronics session, convened by J. Elias, covered electronics development in ATLAS, BaBar, CDF, CMS, H1 and LHCb. In the ionization session, convened by P. Schacht, calorimeters from ATLAS, DO and El58 were presented. Finally, the jet measurement session, convened by J. Terron, covered experiences from ALEPH, CDF, DELPHI, DO, HI, OPAL and ZEUS as well as on-going design studies by linear collider communities in Europe. The Calor2002 scientific program was concluded by the perspective session chaired by R. Wigmans, where perspective presentations by D. Green (High Energy Physics) and J. Krizmanic (Astrophysics) promised continuous interest of the community and pointed out several key issues for the calorimeter development in the future. The Calor2002 conference was attended by more than 150 physicists from different fields and countries. More than hundred presentations were given in the conference, most of which are published in these proceedings. Including convener’s reports, these proceedings contain a total of 114 papers. Also included in these proceedings are two papers which were not presented in the conference: a quartz fiber paper in the Cerenkov calorimetry session and an interesting study on jet energy measurement in the jet measurement session. All conference information, including presentations and proceedings papers, can be found on the Web: http://3w.hep.caltech.edu/calor2002. The credit of the scientific program goes to the members of the IAC and conveners who organized the session and recruited speakers. The success of the conference should also be attributed to the members of the LOC, scientific staff and secretaries who devoted much of their time to make the conference smooth and enjoyable. Finally, credit should also be given to all participants and speakers, both for their efforts in giving presentations and submitting their papers on the due time. The conference is also benefitted by the sponsorship of the Caltech PMA division and three industrial sponsors: Hamamatsu, Kuraray and SICCAS. Ren-yuan Zhu
CONTENTS
Preface
ix
Introduction Historical Review of Calorimeter Developments K. Pretzl
3
Overview and Status of Calorimetry at LHC D. Fournier
17
Calorimetry in Astrophysics S. P. Swordy
43
Considerations for Calorimetry at a Super B Factory W. Wisniewski (contribution not received)
-
Calorimeter Considerations for a Linear Collider Detector R. E. Frey
54
Calorimetry Design with Energy-Flow Concept (Imaging Detector 70
for High-Energy Physics)
V. L. Morgunov
Calorimetry in Astrophysics Covener’s Report T. Parnell
87
ATIC, a Balloon Borne Calorimeter for Cosmic Ray Measurements J. Isbert et al.
89
ATIC Backscatter Study Using Monte Carlo Methods in FLUKA & ROOT T. Wilson et al.
95
A Silicon-Tungsten Calorimeter for Cosmic-Ray Physics V. Bonvicini et al.
101
Electromagnetic Calorimeter for the AMS-02 Experiment R. Kossakowsti et al.
108
Performances of the AMS-02 Electromagnetic Calorimeter P. Maestro et al.
114
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xii
The Status of GLAST CsI Calorimeter A . Chekhtman
121
Performance of GLAST Calorimeter R. Terrier et al.
127
Cosmic Ray Energetics And Mass (CREAM): Calibrating a Cosmic Ray Calorimeter 0. Ganel et al.
133
VERITAS: A Next Generation Atmospheric Cherenkov Detector and Calorimeter for Gamma-Ray Astronomy F. Krennrich
139
Pierre Auger Observatory: The World’s Largest Calorimeter A . K. %pathi EUSO and OWL: Atmospheric Cosmic Ray Calorimetry from Space K. Arisaka (contribution not received)
151 -
Calorimetry (GeV-EeV) in AMANDA and IceCube Neutrino Telescopes J. Lamoureux (contribution not received)
Crystal Calorimetry Performance of a Small Angle BGO Calorimeter at BELLE H. - C. Huang
161
Performance and Calibration of the Crystal Calorimeter of the B a B a r Detector M. Kocian
167
A Systematic Study of Radiation Damage to Large Crystals of CsI(T1) in the B a B a r Detector T. Hryn’ova
175
Performance and Upgrade Plans of the BELLE Calorimeter B. A . Shwartz
182
Development of Yttrium Doped Lead Tungstate Crystal for Physics Applications Q. Deng et al.
190
Performance of PWO Crystal Detectors for a High Resolution Hybrid Electromagnetic Calorimeter at Jefferson Lab A . Gasparian
208
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The PHOTON BALL at COSY R. Novotny et al.
215
Overview of the CMS Electromagnetic Calorimeter P. Lecomte (contribution not received) Performance of the PWO Crystals of the CMS Electromagnetic Calorimeter F. Cavallari
223
Avalanche Photodiodes for the CMS Lead Tungstate Calorimeter R. Rusaclc et al.
231
CMS/ECAL Barrel Construction and Quality Control E. Aufiay
240
Medical Applications Covener’s Report C. Woody
249
Synergies Between Electromagnetic Calorimetry and PET W. W. Moses
251
LSO - From Discovery to Commercial Development C. L. Melcher (contribution not received) New Scintillating Crystals for PET Scanners P. Lecoq A Simulation Framework for Positron Emission Tomography Based on GEANT4 J, Collot et al.
262
274
Silicon Calorimetry Covener’s Report D. Strom
285
Performance of the OPAL Si-W Luminometer at LEP 1-11 G. Abbiendi et al.
287
The ZEUS Hadron Electron Separator, Performance and Experience P. Gottlicher
296
xiv
Design Considerations for a Silicon-Tungsten Electromagnetic Calorimeter for a Linear Collider Detector R. Frey et al.
A Si-W Calorimeter for Linear Collider Physics H. Videau and J.-C. Brient
304 309
Simulation Covener’s Report C. Seez
323
QCD Jet Simulation with CMS at LHC and Background Studies to H -+ yy Process S. Shevchenko et al.
325
Comparisons of Electron and Muon Signals in the ATLAS Liquid Argon Calorimeters with GEANT4 Simulations P. Loch et al.
331
Data Volume Reduction Strategies in the CMS Electromagnetic Calorimeter P. Paganini
339
Performance of CDF Calorimeter Simulation for Tevatron Run I1 C. A . Cumat Simulation of Hadronic Showers in the ATLAS Liquid Argon Calorimeters A . Kiryunin et al. MC Simulation of the ATLAS Hadronic Calorimeter Performance M. J. Varanda Simulation Studies of the Jet and Missing Transverse Energy Performance of the ATLAS Calorimeters M. Wielers Jet Energy Reconstruction with the CMS Detector S. Kunori
345
354 361
367 375
Calibration & Monitoring Covener’s Report M. Gataullin
385
Calibration of the KLOE Electromagnetic Calorimeter C. Gatti et al.
388
xv
Monitoring and Calibration of the BELLE Electromagnetic Calorimeter K. Miyabayashi
394
Calibration and Monitoring of the ZEUS Uranium Scintillator Calorimeter at HERA M.Barbi
401
Calibration of the PHENIX Lead Scintillator Calorimeter
409
H. Torii DO Calorimeter Calibration U.Bassler
413
Calibrating a Longitudinally Segmented Calorimeter 0. Lobban
421
The Calibration of the MINOS Detectors R. Nacho1 et al.
428
First Results from the MINOS Calibration Detector P. Vahle et al.
436
Calibrating the SNO Detector Response A . Hamer
442
Time Calibration of AMANDA: Three Variations of a Theme of To K. D. Hanson
452
Absolute Calibration of Electromagnetic Calorimeter at LHC with Physics Processes L. Xia, T. Hu and R.-Y. Zhu
459
Monitoring Light Source for CMS Lead Tungstate Crystal Calorimeter at LHC L. Zhang et al.
469
LED based Light Monitoring System for the PRIMEX Experiment at Jefferson Lab S. Danagoulian
479
Cerenkov Calorimetry Covener’s Report S. White Influence of Phase Transition on the Optical Transparency of Lead Fluoride Crystals Q. Deng et al.
489
491
xvi
Explicitly Radiation Hard Fast Gas Cerenkov Calorimeter 0. Atramentov
497
Present Status of CMS HF Quartz Fiber Calorimetry Y. One1
504
Calorimetry of the RICE Detector S. Razzaque
515
Radio Cherenkov Detection of High Energy Particles D. Saltzherg (contribution not received) Radiation Hardness Studies of High OH- Quartz Fibres for a Hadronic Forward Calorimeter of the Compact Muon Solenoid Experiment at the Large Hadron Collider I. Dumanoglu et al.
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521
Scintillation Calorimetry Covener's Report M. Cavalli-Sforza
531
Status of the ATLAS Tile Hadronic Calorimeter Production A. Henriques
532
Studies of the ATLAS Tile Hadron Calorimeter Performance S. Ne'meEek and I. Korolkov
538
An Overview of CMS Central Hadron Calorimeter S. Katta
544
Performance and Calibration of the Forward Plug Calorimeter at ZEUS A. Benen
549
Plug Shower Maximum Detector for CDF Run I1 A. Attal
557
CDF I1 Integrated Calorimetry Environment S. Dell'Agnello
563
Borexino: A Real Time Liquid Scintillator Detector for Low Energy Solar Neutrino Study L. Maramonti
570
The MINOS Far Detector Construction and Quality Assurance Testing L. Mualem
578
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A. New Hermetic Electromagnetic Calorimeter Design for Future Collider Experiments E. Kistenev et al.
584
The Tile HCAL Calorimeter for the TESLA Detector, a Status Report V. Korbel
591
Electronics Covener’s Report J. Elias
605
The ATLAS Tile Calorimeter Front End Electronics F. Martin
607
Overview of Liquid Argon Front End Electronics E. Ferrer Ribas
613
First Results with the QIE8 ASIC s. Los (contribution not received)
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Front-End Electronics for the CMS Preshower Detector A . Go et al.
621
The Front-end Electronics for the LHCb Calorimeters D. Breton
627
Front-end Electronics Upgrade for the CDF Calorimeters C. A . Nelson and T. M. Shaw
644
The Electronics of the New H1 Luminosity System V. Boudry et al.
652
The BaBar Electromagnetic Calorimeter in its Third Year of Operation I. G. Eschrich
H1 Calorimeter DAQ Upgrade for HERA-I1 D. Hoffmann, P.-Y. Duval and C. Vallee
658 665
Ionization Calorimetry Covener’s Report P. Schacht
677
Argon Purity Measurement of the DO Calorimeter A . Besson and G. Sajot
679
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The Run I1 DO Calorimeter: Electronics Upgrade and its Performance N. Parua
687
ATLAS LAr EM Calorimeter: Construction and Uniformity of Response S. Rodier
695
Performance of ATLAS EM Modules in Test Beam D. Zerwas
703
The ATLAS Hadronic Endcap Calorimeter M. Fincke-Keeler
712
Performance of the ATLAS Hadronic End-Cap Calorimeter in Beam Tests A . E. Kiryunin
720
ATLAS Forward Calorimeter (FCAL)
K. K.
300
(contribution not received) A High Resolution Luminosity Monitor for SLAC Experiment El58 G. M. Jones
728
Jet Measurement Simulations and Prototyping Studies for a Digital Hadron Calorimeter V. Zutshi (contribution not received) Jet Measurements with the Aleph Detector at LEP2 M. N. Minard
739
Calorimetry Optimised for Jets H. Videau and J.-C. Brient
747
The Jet Calibration in the H1 Liquid Argon Calorimeter C. Schwanenberger
76 1
Setting the Jet Energy Scale for the ZEUS Calorimeter M. Wing
767
Jet Reconstruction at CDF M. Tonnesmann
773
Suppression of Pileup Noise in a Jet Cone A . Savine
781
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D0’s Recent Results and Experiences with the kT and Cone Jet Algorithms J. Krane
786
Jet Measurement in OPAL I. Nalcamura
793
Developments on Jet Reconstruction by DELPHI A. Kiiskinen
798
E-Flow Optimization of the Hadron Calorimeter for Future Detectors S. Magill et al.
806
On the Energy Measurement of Hadron Jets R. Wigmans, 0. Lobban and A . Sriharan
814
Perspective The Future of Calorimetry in High Energy Physics D. Green
837
Future Experiments in Astrophysics J . F. Krizmanic
867
Conference Pictures
881
Author Index
889
List of Participants
895
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Overview and Introduction Chairpersons: R. Y. Zhu and A . Ereditato
K. Pretzl
Historical Review of Calorimeter Developments
D. Fournier
Overview and Status of Calorimetry at LHC
S. Swordy
Calorimetry in Astrophysic
*W. Wisniewski
Considerations for Calorimetry at a Super B Factory
R. E. Frey
Calorimeter Considerations for a Linear Collider Detector
V. L. Morgunov
Calorimetry Design with Energy-Flow Concept (Imaging Detector for High-Energy Physics)
*Written contribution not received 1
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HISTORICAL REVIEW OF CALORIMETER DEVELOPMENTS
KLAUS PRETZL Laboratory for High Energy Physics, University of Bern, 3012 Bern, Switzerland E-mail: pretzlOlhep.unibe.ch Calorimeters are widely used in astro- and particle physics experiments. They provide the means t o explore new physics in an energy range from several eV to more than 1020 eV. An attempt is made to discuss the historical developments of these devices. This report is far from being complete and the author apologizes for possible omissions and misquotations.
1. Introduction Calorimeters belong t o the most important instruments t o measure the energy of neutral and charged particles produced with cosmic rays or with particle accelerators. Their development was very much driven by the quest for new frontiers in astro- and particle physics. Several types of calorimeters have been developed. There are the so-called true calorimeters, which operate at very low temperatures and are used as thermal sensors. Cryogenic calorimeters are the most sensitive devices in the energy region eV to keV. They are frequently used in direct dark matter detection and double beta decay experiments. Then there are the sampling calorimeters, which are based on measuring the energy loss of secondary particles in an active material, which is sandwiched between the absorbing material of the calorimeter. Ionization or scintillation detectors are commonly used as active layers. Sampling calorimeters are among the most frequently employed calorimeters in high energy physics experiments because they are relatively cheap and they can cover a large energy range, typically from GeV to TeV. Homogeneous total absorption calorimeters, like crystals or liquids (Ar, Kr, Xe) have mostly been developed for electromagnetic shower detection. They yield outstanding energy resolutions but they are rather expensive. Cerenkov calorimeters are based on the detection of Cerenkov radiation of relativistic particles in transparent materials. An early example is the lead glass calorimeter for electromagnetic shower detection. Cerenkov calorimeters with enormous dimensions using large underground water tanks, sea water, polar ice and the atmosphere of the earth have recently
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been developed to measure solar, atmospheric and cosmic neutrinos as well as ultra high energy particles (UHEP) in cosmic rays. Large atmospheric calorimeters also make use of the fluorescence scintillation light emitted when particles pass through the atmosphere. The observation of the fluorescence light of air showers in the atmosphere from a space station is planned for the near future. Properly instrumented, the atmosphere would be the largest calorimeter ever put in operation and would enable us to study UHEP with energies in excess of lo2' eV. As of today calorimeters allow us to explore new physics in the energy range from a few eV to more than lo2' eV. It took the ideas and the devotion of many people and hard work to get there. I apologize to all those people whose contributions I omitted or misquoted in my attempt to give a historical review of the developments in this field. 2. Early Developments
One of the early pioneers in developing the art of calorimetry was W. Orthmann, a close collaborator of W. Nernst (Nobel prize winner for chemistry in 1920). Orthmann' developed a differential calorimeter with which he could measure heat transfers of the order of pWatt. Using this true calorimetric technique, he and L. Meitner2 were able to determine the mean energy of the continuous @-spectrum in 210Bi to be E = 0.337 MeV &6%. This value agrees very well with the mean kinetic energy of E = 0.33 MeV of the emitted @-particles. Their measurements contributed to the notion of a continuous ,8-spectrum leading to Pauli's neutrino hypothesis in 1930. Applying this technique to high energy particles would fail, since the temperature increase A T = caused by the energy loss AE of a high energy particle is unmeasurably small ( A T 10-'K for A E lo2' eV) due t o the heat capacity of the large absorber mass (- 10' g Fe) necessary t o contain the shower. Nevertheless this technique was revitalized in the 1980s by the development of calorimeters for dark matter detection (see chapter 9). In 1954 N.L. Grigorov3 put forward the idea of sampling calorimeters using ionisation chambers (arrays of proportional counters) interspersed between thick iron absorber sheets to measure cosmic ray particles with energies E > 1014 eV. The visible energy of the particle Evisible = Jn(x)dx is then determined from the number of secondary particles in the shower n(x) and their in the ionisation detectors. Because of the invisible energy loss energy loss in the absorber plates and in the detector sheets, sampling calorimeters need to be calibrated in particle beams with known energies in order t o obtain absolute energy measurements. In 1957 Grigorov and his collaborators4 constructed a sampling calorime-
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ter in the Pamir mountains, at an altitude of 3860 m above sea level. Their calorimeter also employed 10m2of emulsion sheets, which they placed between 3 lead sheets to study details of the primary interaction. In order to identify corresponding events in the emulsions and the calorimeter, two layers of emulsion sheets on top of each other were used: one fixed in space, the other moved by a certain amount in a certain time interval with respect to the other one. The two emulsion film images were then matched and thus the time of the shower passage determined. In the 1960s high energy accelerators in the USA and Europe became the main facilities to study high energy phenomena. While charged particles were measured with high accuracy in magnetic spectrometers, the energy of neutral particles like photons, 7ro and neutrons could only be measured by calorimetric means. First successful attempts to measure photon and electron energies with compact electromagnetic sampling calorimeters were made at CALTECH by C. Heusch and C. Prescott5. They studied the electromagnetic shower development of electrons and photons in the energy region of 100 MeV to 5 GeV. For that purpose they built two sandwich counters, one out of plastic scintillator and one of lucite material with lead inserts as absorbers. With this they were able to exploit and compare the performance of calorimeters based on the ionization loss of shower particles in scintillators and those based on Cerenkov radiation in plastic materials. They also studied sampling fluctutations and shower containment by changing the thickness of the lead inserts. A similar study for a hadron calorimeter was done by the Karlsruhe group under the leadership of H. Schopper motivated by the idea of measuring n-p elastic scattering at C E R N ~ . With the vision that calorimeters will play a role not only in accelerator experiments but also in experiments on board space missions, R. Hofstadter and his collaborators7 developed large homogeneous N a I (Tl) and CSI total absorption calorimeters. Because of their robustness, CSI crystals were particularly suited for space-born gamma ray astronomy. The persuasively good energy resolutions obtained with these calorimeters also made them powerful tools for studying inclusive 'r7 production in hadron collisions as well as electron and gamma final states in e+e- collisions at SPEAR. Hofstadter's original ideas were later further developed and realised in the very successful CRYSTAL BALL calorimeter at SLAC, with which many of the charmonium states have been discovered.
3. Segmented Calorimeters Large charged particle spectrometers were disigned for exploring the physics in an energy domain which was made accessible by the new large proton accelera-
6
tors at Fermilab and at CERN (SPS) in the early 1970s. At that time the usefulness of calorimetric energy measurements to complement the measurements in magnetic spectrometers was not yet widely appreciated. However, the parton picture of hadrons, strongly supported by the SLAC single-arm spectrometer experiment, demanded a search for parton jets, which would for example manifest their presence by a large transverse energy flow ET in deep inelastic hadron-hadron collisions. For this search, segmented calorimeters covering a large solid angle were developed. Although jets could not be unambiguously identified at Fermilab, ISR and SPS energies, they were clearly detected a.t higher energies in the UA2 and UA1 experiments at the p-p collider at CERN. The extraordinarily successful use of segmented calorimeters in the UA1 and UA2 experiments in discovering not only jets but also the intermediate vector bosons in their decay-channels Z -+ 2 leptons and W* -+ l e p t o n + m i s s i n g E T ( EFiss)made them indispensable tools for future collider experiments searching for the top quark (t + j e t s leptons), the Higgs ( H -+ yy) and SUSY particles (EFiss). In 1973 neutral currents were discovered by GARGAMELLE at CERN. This important step was decisive for future neutrino experiments. To measure neutral current reactions in neutrino detectors required calorimeters of multiton mass with very large dimensions. One of the first upgrades in this direction was initiated by B. Barish and collaborators' of CALTECH. They improved the calorimetric shower detection capability of their neutrino experiment at Fermilab by introducing a wavelength shifting (WLS) read-out of their very large-sized scintillator tiles. The loss of photoelectrons due t o this WLS technique, typically a factor of 10, could be compensated somewhat by using thicker scintillators. However, the main advantage of the WLS technique over the conventional light-guides is its simplicity and the smaller number of readout channels necessary, which is reflected in the lower costs. By reading the light from at least two opposite sides of a scintillator tile, it was even possible to locate the center of gravity of the shower to within a few cm accuracy.
+
4. Segmentation Using Wavelength Shifter Read-out The WLS principle, which was first introduced by W. Shurcliffg, further discussed by R.L. Garwin" and later developed by G. Keil" provided the capability to construct tower-structured scintillation counter sampling calorimeters. Tower-structured calorimeters were an essential ingredient for the jet search, since they allowed to trigger on events with a large transverse energy ET and to determine the jet energy as well as the jet size. Two types of WLS systems were developed: WLS sheets and WLS rods (later replaced by fibers).
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W. Selove12 used WLS sheets for his jet search experiment at Fermilab and D. Wegener13 developed a fine sampling tower-structured electromagnetic calorimeter for the ARGUS experiment at the DORIS e+e- collider. A novel read-out system using WLS rods was introduced by the author14 for the jet search experiment NA5 at the SPS at CERN. By using a different WLS color (yellow) in the electromagnetic part of the NA5 calorimeter15 than in the hadronic part (BBQ green), it was possible to guide the light of both colors in one rod to the two photomultipliers which, by using appropriate filters, were sensitive to either yellow or green light. This way the energy deposited in the electromagnetic and in the hadronic part of the calorimeter could be measured separately. The NA5 calorimeter was the first tower-structured scintillator sampling calorimeter in operation at CERN. It is still in use in the NA49 experiment in the North Area of the SPS. On the basis of the first positive experiences with WLS read-outs, UAl and UA2 at CERN and CDF at Fermilab developed their calorimeters using this principle. The next step was to introduce WLS-doped optical fibers and scintillation optical fibers for the next generation scintillator sampling calorimeters. However, no company in the fiber-producing industry was interested in developing these special fibers with only slim expectations for a large market. In 1982 D. Treiller, P. Sonderegger and the author persuaded J. Thevenin at SACLAY to develop scintillating fibers and WLS fibers for calorimetry. Thanks to J. Thevenin, very soon the first tower-structured electromagnetic calorimeter16 using WLS fibers doped with K27 (BBQ was not successful, since it cracked during extrusion) could be successfully tested. It was later given the name SHASHLIK. Due to its good energy resolution and its relatively low construction costs, SHASHLIK is being used in DELPHI, HERA-B, PHENIX (RHIC) and LHCB experiments. WLS fiber read-out in hadronic tile calorimeters was further developed by the CDF collaboration a t Fermilab. 0. Gildemeister proposed a novel structure for the ATLAS hadron calorimeter, the so-called TILECAL. In this structure, the scintillating tiles and the read-out fibers run parallel to the particles. This design turned out to be cheap and allowed a hermetic construction, projective geometry as well as depth sampling (3 times). Equally promising were the first tests of J. Thevenin’s scintillating fibers used in a prototype Calorimeter. This technique was further developed, leading to the SPACAL17 calorimeter - a t the time a most promising candidate for use in LHC experiments. SPACAL was a compensating, homogeneous, high resolution calorimeter with properties very close to homogeneous calorimeters. However, depth segmentation turned out to be difficult and its production was more expensive than other calorimeters with similar performances. Therefore it finally did not get used in LHC experiments, but its great performance
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was fully appreciated in smaller-sized experiments like CHORUS, H1 backcalo, AMS-2 and KLOE. Mainly for heavy ion physics at the CERN SPS there was a demand for a fast and radiation-hard calorimeter to measure forward energy flow, which was used for the determination of the centrality of the collision. P. Gorodetzkyl* pioneered the development of a quartz fiber/lead calorimeter with a very fast response (6 ns pulse to pulse separation) due to Cerenkov radiation. The radiation resistance of quartz fibers is considerably higher than that of scintillating fibers. However, because of its moderate energy resolution this type of calorimeter is limited in its applications. Quartz fiber calorimeters are employed in the N50, NA52, ALICE (CASTOR), and CMS experiments. 5. Liquid Ionization Chambers
One of the limiting factors of a sampling calorimeter are the sampling fluctuations and the uniformity of response. To reduce both these factors and still keep the sampling calorimeter compact with minimal dead space between towers, W. Willis and V. Radekalg, in the early 1970s, introduced liquid argon (LAr) as active medium. This technique has proven to be highly successful and has been used in many fixed target and collider experiments (R807/ISR, MARK2, CELLO, NA31, SLD, HELIOS, DO, HERA, ATLAS). The development of the LAr ionization chamber technique was also pioneered by the group of J. Engler” at Karlsruhe. Although fine sampling LAr calorimeters surpass the performance of their scintillator counterparts in many respects, they have the disadvantage that they require cryogenics (boiling temperature of LAr is T = 87 K) and high purity of the liquid. In order to overcome the cooling problem, J. Engler and H. KeimZ1 developed liquid ionization chambers which operate at room temperature. They used tetramethylsilane Si(CH2)4 (TMS), which has a relatively high electron mobility. TMS and tetramethylpentane (TMP) have the double advantage of operating at room temperature and being hydrogeneous, providing the necessary presupposition for a compensating calorimeter. A disadvantage is the high degree of purification needed. Warm liquid calorimeters have been proposed for the UA1 upgrade (TMP) and are being used in the CASCADE experiment. In 1990 D. FournierZ2introduced a novel design for a LAr calorimeter, the so-called ”accordeon”,which has practically no dead space between towers and provides better uniformity of response, less cabling (signals can be extracted from the front and back face of the calorimeter) and fast signal extraction due to low capacitance. The ”accordeon” was adopted as electromagnetic calorimeter for the ATLAS detector. In the evaluation of all possible types of calorimeters, CMS chose PbW04 crystals for their electromagnetic calorimeter
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with the argument of obtaining the best energy resolution, while for ATLAS the better uniformity of response and the better angular resolution with the ” accordeon” were decisive. In the mid-1980s C. Rubbia started the development of a LAr total absorption calorimeter for solar and atmospheric neutrino experiments at the Gran Sasso Laboratory. A 600 ton calorimeter has been realized and is going to be installed in the Gran Sasso Laboratory. The ICARUS collaboration plans t o complete the calorimeter to 3 kton to perform a long baseline neutrino oscillation experiment using the CNGS beam from CERN. A LKr total absorption calorimeter has been developed by the NA48 collaboration and is in operation to study CP violation in Kg,L + I T O I T O and Kg,L -+IT+IT- channels. At the Paul Schemer Institute in Villigen a LXe calorimeter is in construction to search for forbidden p + e y decays which, if found, would indicate physics beyond the Standard Model.
+
6. Compensating Calorimeters
Even with minimal sampling fluctuations the energy resolution of hadron calorimeters is mainly limited by large shower fluctuations, which are due to fluctuations in the electromagnetic component (IT’, etc.) of the shower and the invisible energy due to nuclear excitations, muons and neutrinos. It was suggested by C. Fabjan and W. W i l l i ~that ~ ~ some of this invisible energy can be recuperated using depleted 238U plates as absorber. The energy loss will be compensated by the emission of soft neutrons and gammas in fission processes of the uranium. Measurements supported these ideas and the first compensating 238 U/scintillator calorimeter was employed in the Axial Field Spectrometer at the ISR24. Compensation turned out to be essential for a correct jet energy determination and therefore was a main consideration for the design of calorimeters for high energy collider experiments. However, there are also other ways t o achieve compensation, namely by proper weighting of the electromagnetic and hadronic components, as shown by H. Abramowicz et a125for the WA1 calorimeter and W. Braunschweig et a126for the H1 calorimeter. In 1987, mainly due to the detailed work of R. wig man^^^ supplemented by the work of Brueckmann et a128,the compensation effects were fully understood. Wigmans could show that compensation can be achieved with absorber materials other than uranium by tuning the influencing parameters like choosing the appropriate sampling fractions. For example, compensation can be achieved by choosing the thickness of the absorber and of the scintillator as follows: U/sci = 1/1, Pb/sci = 4/1, Fe/sci = 15/1. The crucial role of hydrogen in the active material was clearly demonstrated by measurements of the
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L3 collaboration. LAr calorimeters do not compensate, due to the missing hydrogen. However, compensation can be achieved by prolonging the charge collection time so that the gammas from neutron capture reactions can be detected or by using the above mentioned weighing procedure. In order to achieve the best jet energy measurements large compensating calorimeters were built at HERA (ZEUS: 238U/sci, H1: Pb, steel/LAr) and at the Fermilab collider (DO: 238 U/LAr). However, compensation degrades the energy resolution for electromagnetic showers considerably. Since the search for the Higgs, with its prominent decay channel H + yy, is one of the prime goals at the LHC, the ATLAS and CMS experiments have chosen non-compensating calorimeters with the highest energy resolution capabilities for electromagnetic showers.
7. Other Sampling Calorimeters The high segmentation capability and the relatively low cost were the main arguments for the development of gas sampling calorimeters. All four LEP experiments were equipped with such devices. The modest obtainable energy resolution (- 20%/&?) for electromagnetic showers with such calorimeters is mainly due to Landau and pathlength fluctuations. In addition, gas sampling calorimeters have to cope with stability problems due to temperature and pressure changes. The disadvantages outweighed the advantages such that they were not further developed. In 1983 P.G. Rancoita and A. Seidman” introduced silicon detectors for electromagnetic calorimetry. These calorimeters were further developed by the SICAPO c o l l a b ~ r a t i o n ~Large-sized ~. silicon detectors employing relatively low-resistivity (less expensive) material are appropriate for calorimeters used in experiments requiring compact geometry, fast signal response and operation in strong magnetic fields. Disadvantages are the high cost and the poor radiation resistance of silicon. Nevertheless, they are used in the ZEUS experiment as electron-hadron separator, in the OPAL experiment at LEP as luminosity monitor, and in the PAMELA experiment as imaging calorimeter. Si/W calorimeters are being seriously considered for e+e- linear collider experiments of the next generation.
8. Crystal Calorimeters Following earlier developments using NaI (Tl) crystals for physics at e+e- colliders, the CRYSTAL BALL c ~ l l a b o r a t i o nat ~ ~SLAC demonstrated very impressively the discovery potential of a tower-structured high-resolution crystal
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calorimeter. It made major contributions to the discovery and the better understanding of the charmonium states. Crystal calorimeters are mainly used for electromagnetic shower detection. In later developments, where the CRYSTAL CLEAR collaboration played a leading role, NaI (Tl) crystals have been replaced by denser and non-hygroscopic materials. Among the most popular are: CsI, BGO and PbW04. The production as well as the physical properties of many of these crystals were already studied during World War 11, since fluorescent and scintillating crystals were developed to mark firing tanks or guns for airplane attacks at night. The typical energy resolutions of (1.5% - 3.5%) / obtained with crystal calorimeters have not been reached by sampling devices. Because of their energy resolution and compactness crystal calorimeters have been widely used in collider experiments: L3, CUSB, CLEO 11, KTEV, GLAST, BABAR, BELLE and CMS. One of the notable by-products is the use of CsI (Tl) crystals in medical tomography.
9. Cryogenic Calorimeters In 1935 F. Simon32 suggested measuring the energy deposited by radioactivity with low temperature calorimeters. He claimed that, with a calorimeter consisting of lcm3 tungsten in a liquid helium bath at 1.3 K, one could measure lo-’ cal/sec, which is about 1000 times more sensitive than the calorimeter of W. Orthmann. The argument is that at low temperatures the heat capacity C of a calorimeter is low and a small energy loss A E of a particle in the calorimeter can lead to an appreciable temperature increase A T = AE/C. More recently, the development of cryogenic calorimeters was motivated by the quest for the dark matter in the universe, the missing neutrinos from the sun and the neutrinoless double beta decay. First ideas and experimental attempts were discussed at a first workshop on low temperature detectors (LTD1)33, which was held in 1987 at Ringberg Castle in southern Bavaria. More workshops followed every other year, either in Europe or in the USA. Most calorimeters used in high energy physics measure the energy loss of a particle in form of scintillation light or ionization. In contrast, cryogenic calorimeters are able to measure the total deposited energy in form of ionization and heat. This feature makes them very effective in detecting very small energy deposits (order of eV) with very high accuracy. The use of superconductors as cryogenic particle detectors was motivated by the small binding energy lmeV of the Cooper pairs. Thus, compared to conventional detectors, several orders of magnitude more free charges are produced, leading to a much higher intrinsic energy resolution. The main advantage of cryogenic devices for the direct detection of dark matter particles, so-called WIMPS (weakly interacting massive particles), is
-
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their effectiveness in measuring very low energy recoils and the possiblity of using a large variety of detector materials. WIMPS can be detected by measuring the nuclear recoil energies in coherent elastic WIMP-nucleus scattering. Depending on the mass of the WIMP and the mass of the detector nucleus, the average recoil varies between eV and keV. The most commonly used WIMP detectors are bolometers. E. Fiorini and T. N i i n i k ~ s k ipioneered ~~ the development of bolometers for measuring neutrinoless double beta decay. But also superheated superconducting granules (SSG) for dark matter detection have been developed. This technique was first introduced by H. Bernas et a135for beta radiation detection and later proposed for dark matter and solar neutrino detection by L. Stodolsky and A. D r ~ k i e r The ~ ~ . first generation WIMP experiments with cryogenic bolometers with absorber masses of about 1 kg (CDMS, EDELWEISS, CRESST and ROSEBUD) and with SSG of 0.5 kg (ORPHEUS) are in operation. Larger detector masses of more than 10 kg are planned for the future. One of the big advantages of cryogenic calorimeters over conventional WIMP detectors is their capability of active background recognition, which allows to discriminate between background recoils due t o electron scattering and genuine nuclear recoils by a simultaneous but separate measurement of phonons and ionization in each event. This is possible since, for a given deposited energy, the ionization generated by nuclear recoils is smaller than that generated by electrons. This feature increases the sensitivity for WIMP detection considerably. Mainly for applications other than WIMP detection, calorimeters on the basis of superconducting tunnel junctions (STJ) have also been developed. Cryogenic cameras37 consisting of STJ pixel arrays provide the astronomers with a powerful tool to observe very faint and distant objects and to determine their distance via red shift. Other research areas have also benefited from these cryogenic detector developments, such as x-ray spectroscopy in astrophysics, mass spectrometry of large molecules (DNA sequencing) as well as x-ray microanalysis for industrial applications. 10. Detection of Extraterrestrial Neutrinos
In 1968 R. Davis38 pioneered the detection of extraterrestrial neutrinos and started a new field of neutrino astronomy. In his chlorine detector buried in the Homestake mine in South Dakota he was the first to detect neutrinos from the sun. The neutrino flux, however, turned out to be lower than expected from the standard solar model. His findings were later confirmed by many experiments, such as BAKSAN, GALLEX, KAMIOKANDE, SUPERKAMIOKANDE. They remained a puzzle until very recently, when the SNO experiment confirmed a long-presumed hypothesis, namely that neutri-
13
nos have a mass and, as a result of this, they change flavour on their way from the sun to the earth. Atmospheric neutrino oscillations have previously been found by the SUPERKAMIOKANDE water Cerenkov detector. In order to look for extraterrestrial neutrinos, K. Lande39 and collaborators installed a water Cerenkov detector in the Homestake mine adjacent to the R. Davies experiment. The detector consisted of 7 water tanks, each viewed by 4 PMs on opposite sides of the tank. On January 4, 1974 the detector signalized an event which the experimenters interpreted as a possible antineutrino burst. Unfortunately, such events do not happen very often and a confirmation is practically impossible unless they are also witnessed by other experiments. If for nothing else, these findings wakened the curiosity of researchers to look for more of these events with larger and better detectors. Thus it was around this time that A. Roberts from Fermilab, V. Peterson from the University of Hawaii, R. March of Madison and others started to think about a deep sea water neutrino telescope near the coast of Hawaii. Their ideas later became a project called DUMAND, which was unfortunately discontinued. But it paved the way for the next generation of cosmic neutrino Cerenkov detectors: NESTOR and ANTARES in the Mediterranean sea as well as AMANDA and ICECUBE in the Antarctic ice. Massive calorimeters like NUSSEX in the Mont Blanc tunnel, BAKSAN in Russia, IMB in the Morton-Thiokol salt mine and KAMIOKANDE in Japan, originally designed for proton decay experiments, were, on 17th February 1987, witness to an extraterrestrial neutrino burst, which originated from a nearby supernova explosion (SN1987A). This was the first time neutrinos from a supernova explosion were detected with terrestrial calorimeters. This happy event encouraged all those who had already made plans to set new trends in neutrino astronomy. An interesting new method has been presented by D. Saltzberg at this conference. It is based on the detection of the coherent emission of Cerenkov radiation in radio- and microwaves. Large volumes of natural materials transparent to radio waves may be employed in future for the detection of ultra high energy (UHE) astrophysical neutrinos. 11. The Atmosphere as Calorimeter At sea level our atmosphere measures 1032 g/cm2. Very high energy particles from outer space trying to traverse our atmosphere would find material in front of them which corresponds to 28 radiation lengths and 16.6 collision lengths. Particles from cosmic origin like hadrons, photons or neutrinos interact with air nuclei, producing secondaries that in turn collide with air atoms, leading to extensive air showers (EAS). The most numerous particles in EAS are elec-
14
trons. Electrons traversing the atmosphere produce Cerenkov light, which is directed along their path. On their way, they can also excite metastable energy levels in atmospheric molecules which, after a short relaxation time, emit a characteristic fluorescence light, which peaks at wavelenghts from 330 to 450 nm. In contrast to the Cerenkov light the emitted fluorescent light is isotropic. The emitted Cerenkov and fluorescence light are proportional t o the EAS energy. Thus properly instrumented, the atmosphere can be utilized as a huge calorimeter. It was P. Blackett4’ who, in 1948, suggested to detect the Cerenkov light in the atmosphere caused by penetrating cosmic particles. A. Chudakov and collaborators4’ were the first to apply this idea in 1962 to detect celestial 7rays. Atmospheric Cerenkov light detection was also pioneered by the Whipple telescope on Mount Hopkin, Arizona, in 1987. It consisted of a l0m-diameter mirror dish and a pixel array of photon detectors42. This technique provided information on the direction, shape and energy of the shower as well as on the type of primary particle (cosmic hadrons produce 2 times less Cerenkov light than gammas of the same energy). The Whipple telescope was one of the most powerful early instruments which made major contributions to the study of high energy gamma rays in the energy range of several hundred GeV to several TeV. However, this technique was limited to a relatively small fiducial area yielding low event rates for high energy showers as well as too poor energy resolutions. In a further step the Fly’s Eye detector43 was built to overcome these deficiencies. The Fly’s Eye detector consists of an array of spherical mirrors with a cluster of PMTs mounted in the focal plane of each mirror. It records the fluorescence light, which is caused by ultra high energy cosmic ray showers in the atmosphere. The Fly’s Eye observatory in Utah consists of two detector stations (Fly’s Eye I and 11) situated 3.3 km distant from each other. Fly’s Eye I is equipped with 67 detector arrays and Fly’s Eye I1 with 8 detector units with 120 eyes. Events more than 20 km away from the observatory could be detected, giving rise to a very large fiducial area of about 100 km2 sr. The simultaneous observation from both Fly’s Eye stations allows a stereoscopic reconstruction of an event. From the observed shower profiles the total energy can be derived. However, the knowledge of the energy scale is still a central issue for atmospheric calorimeters. The original Fly’s Eye detector has now been replaced by a new facility called HIRES, which is sensitive in the energy domain of the Greisen-Zatsepin-Kuzmin (GZK) cut-off. Presently under construction is the P. Auger observatory in Malague in Argentina. It will consist of 1600 water Cerenkov detectors and 4 fluorescence ”eyes” spread over an area of 3000 km2. The P. Auger observatory will measure the energy
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and arrival direction of UHE cosmic rays with energies in excess of 10’’ eV. For the future, an exploratory mission probing the extremes of the universe using the highest energy cosmic rays and neutrinos is planned. It is called EUSO/OWL (EUSO for Extreme Universe Space Observatory) and will orbit the earth in 500 km height and observe an area of about 3 . 1O5km2sr of the earth’s atmosphere, being able to detect several thousand air showers above lo2’ eV per year (see S. Swordy as well as K. Arisaka in these proceedings). With this sensitivity the experimenters aim to systematically study the energy spectrum around the GZK cut-off. They also hope to be able to detect relic Big Bang neutrinos through the 20-resonance absorption of cosmic neutrinos with energies > 1021 eV. 12. Conclusions The development of novel detectors is essential for the exploration of new domains in physics. Calorimeters are a very good example for this. Major discoveries, like neutral currents (by GARGAMELLE), quark and gluon jets (by UA2, UA1 and PETRA), W,Z bosons (by UA1 and UA2), top quark (by CDF and DO), neutrinos from the supernova explosion SN1987A (by NUSSEX, IMB, KAMIOKANDE and BAKSAN), atmospheric neutrino oscillations (by SUPERKAMIOKANDE) and solar neutrino oscillations (by SNO) were made with detectors employing calorimeters. The future will provide enough challenges for young people with imagination.
Acknowledgments I am very grateful to P. Grieder, U. Moser, P. Jenni, Ch. Fabjan, E. Lorenz and R. Wigmans for useful discussions as well as for providing me with material for this presentation. I would also like to thank R.Y. Zhu and his collaborators for the perfect organization of this conference and the pleasant atmosphere. References 1. W. Orthmann, Zeitschrift f. Physik Bd 6 0 , 10 (1930). 2. L. Meitner and W. Orthmann, Zeitschrift f. Physik Bd 60, 143 (1930). 3. N.L. Grigorov et al, Zh. Eksp. Teor. Fiz. 34, 506 (1954). 4. V.S. Murzin, Prog. Elemt. Part. Cosmic Ray Phys. 9, 247 (1967). 5. C. Heusch and C. Prescott, IEEE NS12, 213 (1965). 6. J. Engler et al, NIM 106, 189 (1973). 7. E.B. Hughes et al, IEEE NS17, 14 (1970) and NS19, 126 (1972). 8. B. Barish et al, IEEE NS25/1, 532 (1978). 9. W.A. Shurcliff, J. Optical SOC.Vol 41/3, 209 (1951). 10. R.L. Garwin, Rev. Sci. In&. 31, 1010 (1960).
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G. Keil, NIM 83, 145 (1970). W. Selove et al, NIM 161, 233 (1979). W. Hofmann et al, NIM 195, 475 (1982). V. Eckardt et al, NIM 155, 389 (1978). C. De Marzo et al, NIM 217, 405 (1983). H. Fessler et al, N I M A 2 4 0 , 284 (1985). D. Acosta et al, NIM A294, 193 (1990) and NIM A308, 481 (1991). P. Gorodetzky, Rad. Phys. and Chem. 41, 253 (1993) and P. Gorodetzky et all NIM A361, 161 (1995). 19. W. Willis and V. Radeka, NIM 120, 221 (1974). 20. J. Engler et al, NIM 120, 157 (1974). 21. J. Engler and H. Keim, NIM 223, 47 (1984) and 3. Engler et al, N I M A 2 5 2 , 29 (1986). 22. B. Aubert et al, R D 3 coll. CERN/DRDC/90-31 and NIM A309, 438 (1991). 23. C. Fabjan et al, NIM 141, 61 (1977). 24. H. Gordon et al, NIM 196, 303 (1982). 25. H. Abramovicz et al, NIM 180, 429 (1981). 26. W. Braunschweig et al, NIM A265, 419 (1988). 27. R. Wigmans, NIM A259, 389 (1987). 28. H. Brueckmann et al, NIM A263, 136 (1988). 29. P.G. Rancoita and A. Seidman, NIM 266, 369 (1984). 30. G. Barbiellini et al, NIM A235, 55 (1985) and E. Borchi et al, CERN-EP/89-28 (1989). 31. M. Oreglia et al, Phys. Rev. D25, 2295 (1982). 32. F. Simon, Nature 135, 763 (1935). 33. Low Temperature Detectors for Neutrinos and Dark Matter, ed. K. Pretzl, N. Schmitz, L. Stodolsky, Springer, Berlin (1987); see also K. Pretzl, Proceedings of "Calorimetry in High Energy Physics" World Scientific, 32 (Lisbon 1999). 34. E. Fiorin i and T.O. Niinikoski, NIM 224, 83 (1984). 35. H. Bernas et al, Phys. Lett. A24, 721 (1967). 36. A. Drukier, L. Stodolsky, Phys. Rev. D30/11, 2295 (1984). 37. T. Peacock et al, Astron. Astrophys. Suppl. Ser. 127, 497 (1998). 38. R. Davies et al, Phys. Rev. Lett. 20, 1205 (1968). 39. K. Lande et al, Nature 251, (Oct.11.1974). 40. P. Blackett, Rep. Gassiot Committee 34, UK (1948). 41. A. Chudakov et al, J. Phys. Soc. Japan 17/AIII, 106 (1962). 42. M. Cawley et al, Experimental Astronomy 1, 173 (1990). 43. R.M. Baltrusaitis et al, NIM A240, 410-428 (1985). 11. 12. 13. 14. 15. 16. 17. 18.
OVERVIEW AND STATUS OF CALORIMETRY AT LHC
D. FOURNIER Laboratoire de 1’Acce‘le‘rateurLine‘aire - Centre Scientzfique d ’Orsay - B.P.34 - 91898 ORSAY CEDEX (FRANCE) E-mail: fournierOlal.in2p3.fr
1. Introduction Calorimeters play a central role in “general purpose detectors’’ for high energy proton-proton colliders, like ATLAS and CMS at the LHC: they allow to trigger, to identify and to measure electrons, photons and jets, as well as escaping neutrinos or other non-interacting particles appearing as missing transverse energy. They also complement muon detection both at the trigger level, and in providing an estimate of the energy lost in traversing them. Indeed calorimeters are only one part of the experimental set-up, and the overall optimisation of the experiment, i.e. reaching optimal combined performance with the tracker, the magnets and the muon systems was one of the most challenging tasks of the designers. Today, both ATLAS and CMS ca!orimeters are well in the construction phase. This is a time when one realises that some choices were indeed wise, when the detector will meet or sometimes exceed the specifications, without having caused too much trouble in the engineering phase. But there are also cases for which compromises had to be made, in order to cope with technical difficulties, budgetary constraints, and schedule. Taking in turn, electromagnetic, hadronic and forward calorimetry, the talk addresses, for ATLAS and CMS: - design evolutions since the Technical Design Reports (TDR)
- update of performances (test beam results, simulations) - systems aspects
- status of construction At the end, the particular cases of LHCb and ALICE are briefly considered.
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2. EM Calorimetry
2.1. ATLAS EM Calorimetry 2.1.1. Main features of the design The ATLAS EM calorimeter uses the Liquid Argon technique, for its excellent stability and radiation resistance, with an “accordion geometry” to allow for hermeticity, speed and high granularity’. The barrel part which covers up to r] = 1.4 is separated in two cylindrical “half-barrels”, housed in a single cryostat which shares its isolation vacuum with the solenoid (figure 1). Each half-barrel is made of 16 modules and is preceded by a thin presampler layer. In the end-caps (figure 2), each EM wheel (made of 8 modules and covering 1.4 < r] < 3.2) is preceded by a thin presampler for 1.5 < r] < 1.8. The design energy resolution is l O % / a , with a constant term of 0.7%. The granularity and noise. (which was measured in beam tests with ATLAS-like electronics) are as in table 1. Thanks to the separation in 3 layers in depth, the front strips and central cells allow to measure the direction of photons, independently of the knowledge of the interaction vertex, with an accuracy of 50 m r a d l a . The front-end electronics scheme, unchanged since the TDR, features 3 gains (1, 10, 100) shaping amplifiers, analog buffering in SCAs (switch capacitor arrays) every 25 ns, and digitization of a given number of samples (typically 5) upon LVLl request.
WADOWMAR0
COID-lU-MRU CARIR P A 1 3 PAPNEL
’-
\
\\~I‘AHY
\
PRESAYPlbU
VWCL
COIJ VkXSEL
Figure 1. Sketch of ATLAS E M barrel liquid argon calorimeter (only one half is shown).
In this scheme (figure 3), the largest non-saturating gain is first chosen by digitising, in medium gain, the sample closest to the expected signal maximum. Then all samples are digitised with the same gain, allowing then to use digital filtering for combined optimisation of noise and pile-up as a function of
19 Table 1. Granularity and noise of ATLAS EM calorimeter.
Figure 2.
Sketch of ATLAS end-cap liquid argon calorimeters (one side).
luminosity.
Figure 3.
Simplified readout diagram of liquid argon calorimeters.
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2.1.2. Difficulties with engineering and fabrication
Essentially three difficulties were met: 0 Fabrication of large electrodes: In the early prototypes3, 3-layer, flexible, copper-polyimide electrodes were built with the standard laminates and processing equipment, limited to 60 cm width. Sticking to this approach would have resulted in 7 electrodes to match one absorber, between q = 0 and q = 1.4, with the drawback of several thin cracks. It was thus decided, in 1996, to move to l m width laminates and processing equipment, in order to cover the same area with two electrodes only. It took several years, in collaboration with firms, to reach a satisfactory quality and rate of production. The tuning of non-standard equipment was made more acute due t o the presence, on each electrode, of almost 1000 serigraphied resistive pads, necessary t o distribute high voltage. The resistances proved rather fragile, in particular when bending electrodes to the desired accordion shape (figure 4). At the time of the conference, more than 75% of the 6000 electrodes of the calorimeter were available.
Figure 4.
View of one central barrel electrode (7= 0.0 - 0.8).
HV trouble shooting: Each electrode is kept in its nominal position, in the middle of the gap between two absorbers, using honeycomb bands linked by a set of wires in a sort of net matching the accordion waves (figure 5). The total area of the material used is about 20000m2. The nominal high voltage of lkV/mm in liquid argon is also used as test voltage in air. In the early phase of the stacking, done in clean rooms with controlled temperature and humidity, unexpected spurious sparkings, and even some shorts were experienced. A suitable mode of operation could be found only after that a thorough cleaning of honeycomb nets, followed by a specific HV training of each of them was installed. 0 Rad hard electronics: The front-end electronics resides in front-end crates, at the high q end of each cryostat, and rather large radius (- 2.5m), where the level of radiations is reduced n/cm2 and 30Gy each high luminosity
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year) and accessibility is possible. All electronics on these boards was revisited in the last two years such that only radiation-hard processes be used (mostly DMILL). The SCA controller, originally planned in DMILL appeared to have a too low yield. It was redesigned in a 0.25 micron process and is now becoming available.
Figure 5. Close view of the transition between large and small wheel in an E M end module, showing the honeycomb nets.
A set of 30 boards to fill a full front-end crate will be available as of fall 2002, and submitted to detailed tests before series production of boards starts. Most custom designed chips (preamplifiers, shaping amplifiers, SCAs) are already mass produced and being subjected to acceptance tests. 2.1.3. Test beam results After thorough tests of “module 0s” in year 1999 and 20004, which revealed a few problematic points, later corrected (see below), two series modules of both the barrel and the end-caps were tested in beam in summer 2001 (see dedicated talks to this conference). The main problem encountered was to understand in detail the behaviour of fast signals (peaking time of 50 ns), in complex structures: from the electrode cell sensing the current signal in the module, to the preamplifier on the front-end board, are: the traces routing the signal (and ground !) out on the
22
electrode, the summing board, the mother board, cold cables, feedthrough and crate baseplane. Inductances and impedance discontinuities are affecting the physics signal (and the calibration signal injected at the mother board level) propagation, making the electronics calibration to the anticipated level (channel to channel dispersion of 0.25% rms) a more difficult task than anticipated. Problems were best seen from the scan of a module on constant q or constant q5 lines: the energy response should be flat, and was not. The results for series modules are now quite good, but one had to:
- improve the ground return on the electrodes, - re-route the traces on mother boards and summing boards,
- use rather complex formalism to analyse the pulse shapes. Combining in the same histogram (figure 6 ) all electrons from the scan of a production module 600 middle cells) with 245 GeV electrons gives a total resolution of 1.14% which splits more or less equally between the sampling term (0.7%) and the constant term (0.9%). Some corrections, like for the transition between electrodes at 7) = 0.8, or correcting some sick electronics channels, are still to be done. (W
2.2. CMS EM calorimetry 2.2.1. Main features of the design and evolution since TDR In CMS a PbW04 crystal calorimeter5 was chosen for its excellent sampling term of the energy resolution, and for its compactness (the radiation length of PbW04 is 0.9 cm). R&D concentrated on purification and controlled doping of the base material, and crystal growth conditions, in order to avoid as much as possible radiation dependent effects. The rather low light yield called for active light converters (APDs, VPTs) which also needed a specific development. The CMS EM calorimeter consists of two half-barrels, each made of 18 identical modules, and two end-caps each made of two Dees (figure 7). An evolution from the initial proposal, is that now only the endcaps are preceded by a Lead-Silicon preshower . The sampling term of the energy resolution is thus about 3 % / a for the barrel and 5 . 5 % / a for the end-caps. 2.2.2. Readout and noise The scintillation light from the crystals which has a broad spectrum around 420 nm, is converted -in the barrel- to an electrical signal by two APDs (25
23 iss
Figure 6 . Combined spectrum of 245 GeV electrons taken over not yet adjusted).
Figure 7.
N
600 cells (absolute scale
Geometry of the CMS crystal calorimeter.
mm2 each) glued on the back face of each crystal. In the end-caps, the solenoid magnetic field, almost parallel to the crystal direction, allows the use of 3-stages
24 Table 2. Granularity and channel count of the CMS crystal calorimeter.
I
A17XW
Barrel I 0 . 0 1 7 5 ~0.0175 17 < 1.48 End-cap Variable 1.48 < 17 < 3.0 End-cap preshower
I
Cell size (mm)
I
I
213x213
I
I
I
Depth (Xo) 25.8
I
Number of
I
61200
I channels
29.6 x 29.6
23
15632
63 x 1.9
3
N
I
130000
photo-multipliers (VPTs), less sensitive to radiations than APDs. A tight Quality Control is applied t o the production (see dedicated presentations to this conference). One of the criteria is a combined crystal-APD efficiency of more than 6 photo-electrons/MeV, measured with a radioactive source (Co60). The electronics noise depends both on this efficiency, on the APDs ”excess noise factor” ( w 2.2), and on the preamplifier characteristics. The current estimate is around 35 MeV/crystal (this figure is expected to approximately double after 10 years of high luminosity running, because of the shot noise associated t o the APDs’ leakage current). In the end-caps, read out by Vacuum Photo-Triodes, it is about 50 MeV. The preamplifier (figure 8) is followed by a 4 gain shaping amplifier (single RC-CR filter with a 43 ns time constant, with gains in the ratio 1, 5, 9, 33). The sample and hold system selects at 40 MHz the largest non saturating gain for digitisation in the fly. This means that the 5 or 7 samples used for a given pulse are, for large signals, taken with different gains. This system is called ”floating point preamplifier” since it provides to the downstream stage (ADC) a sampled analogue level, and two bits for the gain. Evaluations are still ongoing in the collaboration to decide if all ADC samples are continuously transmitted at 40 MHz (one 1.3 GHz fibre per crystal) for treatment outside of the detector, or if LVLl primitives (5 x 5 crystals) are formed locally, allowing to output only events (stored locally in a memory) selected by LVL1. The understanding after dedicated talks at the Conference was that the second way is more likely to be chosen, in particular because of financial constraints. 2.2.3. Short term follow-up of light output Exposed to low radiation levels (one Gray per hour or less), like in standard LHC conditions, PbW04 crystals show a small drop of light output (mostly due to absorption by colour centres), which saturates after a few hours of exposure, and is followed, when irradiation stops, by a recovery with a time constant of
'25
Figure 8. Simplified diagram of the CMS calorimeter front-end readout.
.;!
:.!irradiation ., i i
;
,
.j
i
j
.
:
111
B i
I,
I
Monitoring light Figure 9.
111
Ill
(11
11,
Ill
W,.,l,,,lh
Ill
IJI
(,I
Geometrical distribution of light, and frequency spectrum.
typically hours as well (figure 10). In order to limit the consequences of this dependence, the following actions were taken: Production crystals are requested to vary by less than 6% under exposures like above. In order to follow the crystal behaviour at the required pace (hours) during LHC data taking, an optical switching system will send in sequence laser light pulses (at 440 nm) to all crystals of each module. Because the laser pulses do not have a spectrum identical to the scintilla-
26 c
1.01
$
1 0.99
I? Green Cusor r?mitor;ny 0 Blue laser rnonitA 1 2 0 GeV skctronr
0.98 0.97
0.90
0.95 0.94 0.93 0.92
0
1
2
3
4
6
7
time Idayl
Figure 10. Simulated behaviour of crystal response to electrons and light pulses (green, blue) as a function of time.
tion light, nor the same geometrical distribution in the crystal, the correction cannot be perfect. It was estimated, and confirmed by exposing pre-production modules to test beam6, that the constant term associated to the residuals of the laser monitoring will not be larger than 0.4%.
2.3. System aspects While the behaviour of the basic ”bricks” of both ATLAS and CMS electromagnetic calorimeters is now well understood, the performance of EM calorimeters as “systems” still critically depends on many integration issues. A selection of the most relevant ones is considered below. 2.3.1. Effect of tracker material and magnetic field The strong requirements (granularity, speed) on tracking systems has lead to central tracking detectors which are unfortunately rather massive, as illustrated by the CMS case in figure 2.3.17 (ATLAS is similar)s: Electrons and photons are thus subject to early showering in the tracker (plus solenoid and cryostat in the case of ATLAS) before reaching the active calorimeter (or presampler) medium. The low energy calorimeter tail subsequently generated is particularly visible in CMS due to its better energy resolution, and larger magnetic field (4T for CMS, 2T for ATLAS). Figure 2.3.1 shows the energy spectrum of electrons after that an isolation criterium is applied at the trigger level (adding a 6% inefficiency), and reconstructing the shower with an ”hybrid cluster” (i.e. extended to sub-clusters in the azimuthal direction). In the same conditions, for 35 GeV ET, the position resolution, converted to angular resolution assuming a fixed vertex is about 1.0 mrad in 17 and 2.1 mrad
27
Figure 11. (a): Material in the CMS tracker; (b)Simulated electron energy spectrum (normalised to true energy) in the CMS detector.
in 4. For comparison, with the middle sampling of ATLAS the corresponding figures are 1.0 and 1.5 mrad respectively. Once more the worse resolution in azimuth is to be associated with the effect of bremsstrahlung . Photons which do not interact before a radius of -90 cm are much less affected than electrons. In CMS, for a 110 GeV Higgs decaying into yy, 78% of the reconstructed masses without conversion fall in a 1.9 GeV mass bin. However, the efficiency of the ”non-converting” photon cut alone is about 70% per leg. In ATLAS using both interacting and non-interacting photons the 80% acceptance mass bin is 3.1 GeV wide. The comparative performances of the two experiments for H + yy detection depend on the resolution that CMS will reach with the converted photons, and on several other aspects (background rejection, pointing - see below). 2.3.2. Calibration in situ
In ATLAS it is assumed (and now confirmed by beam test of series modules) that the detector is uniform ”by construction” to better than 0.4% rms in areas of Aq x Aq5 = 0.2 x 0.4 or larger. Taking this as “minimal hypothesis”, there would be 440 areas (0.2x0.4) to be intercalibrated in situ. It was shown by simulationsg that imposing the Z mass constraint to 2 + e f e - decays measured in the calorimeter only (i.e. without reference to tracking information) an adequate inter-calibration (0.3% rms cell to cell dispersion) can be obtained with data recorded during 48 hours at low luminosity (where the rate of 2 -+ e+e- is about 1 Hz). The same constraint gives indeed an extremely precise absolute energy scale calibration. In CMS the crystals are first calibrated in the laboratory with laser pulses
28
and/or radioactive sources. Experience shows that the correlation of this calibration with the response to high energy electrons from beam tests is not better than 6% rms. In the likely c a e that all crystals cannot be calibrated in test beam, the in-situ inter-calibration will use lab results as starting point. The currently developed strategy is based on using electrons from W decays, measured with the tracker. This is better adapted than the Z mass constraint, due to the higher rate. Preliminary studies" indicate that two months of low luminosity data are necessary to intercalibrate to 0.5% rms in this way. When this is done, Z decays give the absolute energy scale. Considerations on azimuthal uniformity of response to minimum bias events may help in this inter-calibration task.
2.3.3. Constant term Besides the residual of the crystals or cells inter-calibration, and of short term variations, like the crystal output light depending on recent irradiation history, there are several contributions to the constant term. One of them is associated with temperature dependence of signal response: the temperature dependence of the liquid argon signals was measured t o be -2%/OK (see ref 1, chapII, p.33). The liquid argon bath is subject t o free convection, which can be turbulent in some places despite the small gradients (the viscosity of argon is very low), and is therefore difficult to simulate. The total heat influx is about 2.5 kW per cryostat. Extensive finite elements simulations (preliminary) indicate an overall temperature dispersion within the barrel sensitive volume of f 0.15 degrees, hopefully small enough to avoid the need for corrections. In case of larger gradients, corrections will be possible offline, thanks to continuous recording of -300 precision temperature probes located at the surface of modules. 0 In CMS the temperature dependence of "crystal+APD" is about -4.3%/OK. Removing the heat dissipated by front-end electronics (2 W per channel, i.e. 160 kW in total) right in the back of the crystals, while keeping an excellent temperature uniformity, is a challenge. A thermal analysis of the crystal calorimeter was made, based on the use of pressurised water circulating in a dense pipe network, separated in three layers, each layer being isolated from the more external one by thermal shields. As a result, it is estimated that a temperature dispersion of f 0.05'K within the crystal volume can be reached. Overall, ATLAS claims a constant term in the energy resolution of 0.7%, and CMS of 0.55%. At this stage it might be useful to stress that those figures will only be reached if processing key physics channels (W+ ev, Z+ ee) is easy, with a fast turn-over, as of LHC start-up.
29
2.3.4. Use of granularity Background rejection: In the search for the Higgs in two photons (up to 150 GeV) it is necessary to bring the background from jet-jet and y-jet events well below the irreducible yy background. After standard shape cuts the remaining background is dominated by jets fragmenting to single r0s. Using the high granularity of the calorimeters the performances reported in table 3 were obtained by simulation, at 50 GeV ET. Somewhat inferior in the barrel, CMS is equivalent or slightly better in the end-caps,thanks to the high granularity of its lead-silicon preshower. Table 3.
rejection in ATLAS and
ATLAS(al1 y) CMS (unconverted)
0-0.45 3.6 3
0.45-1. 3.1 2.2
1.-1.5 2.6 2
-1.7 3.1 3.5
-2.4 2.8 2.5
Pointing: The measurement of the direction of non-converted photons is a unique feature of ATLAS (indeed measuring the direction of converted photons is easy in both detectors). Such direction measurements are important in several cases, in particular for Higgs decaying in two photons, where the direction error contributes t o the mass resolution (at high luminosity, the interaction vertex is often ambiguous for yy events). Gauge Mediated Susy Breaking models, in which the neutralino photon-gravitino i decay may have a long enough life time to produce “non-pointing photons”, which can be used t o sign the process, is another example where pointing is useful.
2.3.5. Linearity Excellent linearity is required for precision physics. One topic particularly demanding is an improved measurement of the W mass using the W -+ ev channel. Illustrated below is the linearity observed in one of the best calorimeters built so far, namely the homogeneous krypton Calorimeter of the NA48 CP Violation experiment at CERNll (figure 12). Over the energy range of interest for this experiment, the systematic uncertainty was estimated to be 6 rms. What would be needed to meet the W mass measurement requirement (25 MeV error, overall) is gaining a factor of 3, however on a restricted range (Mz/2 to Mw/2). This would probably be possible with the NA48 calorimeter, ... but ATLAS and CMS calorimeters are more complex devices, and not much was done so far to assess them, in this respect, at the required level.
30
1.002
1
.
(E+45MeVf/pjrom ,K
t.mi 1
0.969
0.ws 0.997
0.96'6
Energy (GeV) Figure 12. Ratio of electron energy, measured with the krypton calorimeter, and momentum from the magnetic spectrometer, in NA48.
2.3.6. Data reduction Large number of cells, large dynamic range, and high trigger rates produce very large amount of data (-1.0 Mbyte/event for the calorimeter itself, in both experiments). The associated cost for storing and processing these data was recently put under scrutiny12, which triggered some further dedicated work in the collaborations. One route for data reduction being explored by both ATLAS and CMS, is "zero suppression". While at first sight cutting cells containing "only noise" is rather tempting, this may generate subtle adverse effects on precision physics, difficult to resolve later on. Detailed Monte Carlo evaluations (and control samples) will be needed before such a data reduction can be implemented at the "on line" level, but prospects are interesting13. 3. Hadronic Calorimetry
All the electromagnetic component of jets, plus a fraction of the charged hadronic part, is deposited in EM calorimeters representing 1 to 1.5 interaction length A. EM calorimeters being calibrated with electrons, the energy measured for jets has to be converted to "hadronic scale" when, as it is the
31
case for ATLAS and CMS the electron to hadron ratio (e/h) is larger than 1. To catch the remaining part of jets, more massive devices are needed, the “hadronic calorimeters”, up to a total thickness of 9X or more. Full coverage in pseudo rapidity is mandatory, up to q N 5. The instrumentation of the most forward region (3 < q < 5) raised specific problems. This part is considered in the next section. N
3.1. CMS hadronic Calorimeter CMS uses scintillator sampling calorimetry both in the barrel and in the endcaps (up to q = 3.0)14. The choice to place the full calorimeter inside the coil imposed a non magnetic absorber (brass, in plates of 5 cm). The constraint of the coil size (inner radius 2.95 m, outer radius 3.80 m) in practice limited the total thickness at q =O to 7 A. In order to improve on this figure, it was found necessary to add a ”tail catcher” behind the solenoid coil, for a total of 9.4 A, compromising to some extend-in a limited pseudo rapidity range-the original design criterium. Scintillator tiles (3.7 mm thick) inserted in between the brass plates, are readout by wave length shifting fibres, fitted in grooves. The former are glued to clear fibres which bring light out of the solenoid, up t o Hybrid-PhotoDetectors (proximity focused single stage photomultipliers with ” pixelised” silicon diode target) able to work in the fringe magnetic field. The light yield is about 10 pe/GeV. The granularity is 0.087 x 0.087 (5 x 5 EM towers) with 3 samplings in depth, the first one being rather thin in order t o sample the particles coming out from the ECAL. Close to the upper ( q = 3) boundary, the cumulated radiations (3 lo4 Gy integrated over 10 years) will start to affect the collected light (mostly because of a reduction of the WLS fibre absorption length). This will be monitored by a moving source, and using LHC data itself. 3.2. ATLAS Tile Calorimeter ATLAS uses scintillator sampling calorimetry in the barrel and in the extended barrel, up to q = 1.715. The iron plates (5mm thick, grouped by 3) and scintillator plates (3mm thick), are perpendicular to the beam axis. The thickness up to the last active layer is 9 X at q=O. The scintillation light is collected by WLS fibres running on either side of scintillator plates. This allows a rather easy bundling of fibres to form towers, read out by photomultipliers located in the “girders” (outer radius 4.23 m). At this place the solenoid and toroid fringe fields are low, and further reduced by shielding with high permeability metal sheets.The light yield is about 40 pe/GeV. The granularity is 0.1 x 0.1 (4 x 4 EM towers) with 3 samplings in
32
depth (the last segment has a granularity of 0 . 2 ~ 0.1). Towers are pointing in azimuth, and pseudo pointing in 77. 3.3. A T L A S Hadronic End-Cap
Beyond 77 = 1.5, ATLAS uses the Copper-Liquid Argon technique’. Among other aspects this alleviates radiation resistance problems. The detector consists of two wheels-HEC1 and HEC2- in the same cryostat as the Electromagnetic end-cap and Forward calorimeters (see figure 2). The copper plates (25mm thick in HEC1, 50 mm in HEC2) are perpendicular to the beam axis and interleaved with 4-uple liquid argon gaps in a configuration of electrostatic transformer. Pairs of adjacent cells in depth are connected to a preamplifier located in the liquid, at the periphery of the wheels. Summing of signals to form readout towers is done downstream of the preamplifiers, in the cold as well. This scheme gives adequate speed of response, with signal rise-time of N 50ns. The granularity is 0.1 x 0.1 (4 x 4 EM towers) up to 77 = 2.5 and 0 . 2 ~0.2 up to 77 = 3.2, with 4 samplings in depth (at the time of the TDR, the two segments of HEC2 were ganged together).
3.4. Resolution, linearity Prototypes of the hadronic calorimeters briefly described above have been tested in high energy pion beams, both in ”standalone” mode, and with their EM counterpart in front. In all cases the electron to hadron response ratio (e/h)is greater than 1, both in the electromagnetic and hadronic compartments, which affects both the linearity and the constant term. The example of the CMS calorimeter16 is summarised in figure 13. With a suitable weighting, depending on signal height on an event by event basis, the combination crystal calorimeter-hadronic calorimeter can be made nearly as good as the hadronic part in stand alone. Results from the ATLAS combined LAr-Tile prototypes17 show a similar behaviour, as given in figure 14. Cell by cell weighting (a la H1) improves by 15% the resolution of the “benchmark” method, with a single weight per compartment. Performances have also been extrapolated to jets at LHC. A larger cone size improves the sampling and constant terms of the energy resolution, but the fluctuations of the noise and pile-up soon become dominant. Cone sizes down to 0.4 are used for the high luminosity case. Some relevant parameters are summarised in table 4 (the pile-up is the expected value a t nominal high luminosity in a cone AR=0.7). Attempts are being made in CMS to improve the jet resolution by using
-
33
s
0 Combined 96 (benchmarks)
0.3
*
n interocting in ECAl or HCAL
0
Combined 96 (HI weighting)
no weighting passive weighting
0.2
dynamic weighting
0.1
n U I "
0
'
" " '
SO
IW
'
, ' . I , . ' . .
IS0
'
"
,'
"
1
2W ZSO JW IS0 JCU pion beam momentum (GeV)
Figure 13. Pion resolution with prototypes of the CMS calorimeter.
0
0. I
0.2
0.3
11.1 Ekiu,, (GeV-") Figure 14. Pion resolution with prototypes of the ATLAS calorimeter.
Table 4. Performances of ATLAS and CMS hadronic calorimeters
the tracker information'', on the basis of what was done, with some success, in some LEP experiments and elsewhere. The so-called "energy flow" approach consists mainly in replacing the energy of each somewhat isolated charged hadron measured in the calorimeter, and linked to a track, by the corresponding momentum measured in the tracker. As an example, the energy resolution of 100 GeV jets is improved from 12 to 8 GeV (simulation done in a low luminosity case). While this looks promising, systematic effects associated to the method need to be evaluated case by case, depending on the physics analysis undertaken.
3 .5 . In situ Calibration 0 Z+jet: Given its cleanliness and high cross-section, this channel is particularly attractive to calibrate jets to the lepton scale of selected Z decays, by transverse momentum balance. ATLAS simulations showed that, with a veto on extra jets and/or an alignment cut in the transverse plane (A4 cut), the energy bias can be kept at the few % levelg (see figure 15).
34 N4.08
3
-
-
0
a” d 0.06 a”
Full simulation
v
0.04
-
0.02
: Q
-
0
-
0
-
-
-0.02 -1
-0.5
0
0.5
I 1
1 1 1 1
1 1 1 1
1 1 1 1
1 1 1 1
L
I
Figure 15. Jet calibration with 2 + j e t s events. Left: relative p l difference between 2 and jet, for p l >40GeV.Right: evolution of the average fractional imbalance with p l jet.
The method is also suitable t o calibrate b-jets (tagged with a displaced vertex), and forward jets by selecting events with the jet in the forward direction, while the leptons of the Z are kept central. The other main tool consists in imposing the W mass constraint to W -+ jet-jet decays suitably selected. This method is particularly well adapted to top mass measurements, using the event sample itself. 3.6. Some illustrations
To illustrate the methods briefly described above, a selected sample of results obtained in ATLAS by s i m ~ l a t i o n ’are ~ shown below: 0 Measurement of the top mass: It is presently estimated that, with the statistics of one year at low luminosity (10 fb-’) the systematic error on the top mass measurement, using the 3-jets decay mode, can be brought down to 1% (figure 16). 0 Higgs associate production: The discovery of a Higgs boson above the LEP exclusion limit, up to ~ 1 3 0 G e Vwill be difficult at LHC and requires several modes. The associated t-t H, H -+b b mode can usefully complement H-+ yy if the two b-jet mass resolution is good enough, and the background well understood. A simulated spectrum, with signal (120 GeV) and background is shown in figure 17.
35
t
2000
c 0
ll 100
200
300
400
mjjb(GeV)
Figure 16. Invariant jjb mass from top decays (loft-’ integrated luminosity). The background (shaded) is dominated by ”wrong combinations”.
Figure 17. Invariant mass of tagged b-jets pairs, above background, for associate t fH production and 1OOfb-1 integrated luminosity.
4. Forward Calorimetry 4.1. A harsh region
The first ”raison d’i5tre” of forward calorimetry is to avoid tails due to particles escaping around the beam pipe, in the measurement of missing ET. For practical reasons, it is difficult to instrument beyond q =5. This is in general adequate, although some channels where precise measurement of ET is necessary would benefit from an extended coverage (H+ TT at low luminosity is such an example). At shower max and q = 4, in ATLAS, the neutron flux is about 3 1015n/cm2/year, a factor 1000 above the barrel EM situation. The main constraint in designing these devices was thus their survival to 10 years of high luminosity. Enough granularity at high pseudorapidity is necessary in order that the relative precision on jet direction do not spoil the relative energy resolution. A summary of specifications and general parameters, for ATLAS and CMS, is given in table 5 below: 4.2. The CMS Hadronic Forward Calorimeter
CMS chose to recess the front face of their hadronic Forward Calorimeter (HF) at l l m from the collision point and to base the detection on Cerenkov light produced in quartz fibres embedded in a metal matrix (figure 18), with a pitch of 2.5 x 2.5 rnm2O.
36 table 5. Parameters fo ATLAS and CMS Forward Calorimeters.
ATLAS Technique Tungsten-Liquid Argon 3.1 < 71 < 4.9 Geom acceptance Layers in depth 3 Number of channels 1792fside Sampling term 9O%/JE Constant term 8% Noise pile-up * 6 GeV ET in R = 0.4 at high luminosity
+
-
CMS iron-quartz fibres 3.0 < 7 < 5.0 2
2096fside 200%/dE -10% 6 GeV ET
-
Figure 18. Central part of a CMS HF module, prior to fibre insertion.
This approach samples mostly the neutral component of the shower, and thus features a large e/h ratio. The detector sensitivity is 5 1 pe/GeV. Despite the high radiation tolerance of quartz it is expected that the light from the most central part of the device will be reduced by -30% after 10 years at high luminosity, this being mostly due to an effect on the fibre cladding (figure 19).
4.3. The ATLAS FCAL The choice of ATLAS was to integrate the forward calorimeter in the same cryostat as the EMEC and HEC calorimeters. The structure chosen is a metal
37
Figure 19. Simulation of radiation damage on light yield from fibres of the CMS HF.
matrix with holes parallel to the beam axis, in which tubes with rods are inserted (figure 20).
Figure 20.
Structure of the ATLAS Forward Calorimeter.
To avoid spill-out of showers, a dense calorimeter was mandatory, which dictated the use of Tungsten for the hadronic part (average density is 14 g/cm3). Radiation resistance of liquid argon made the device possible, even with its front face at 4.7 m from the collision point. The other adverse effect due to the high rates is space charge build-up. The tolerable flux goes like V2/d4p ( p is the ion mobility) and calls for extremely thin gaps. ATLAS chose d=250 microns in the first (EM) section and 375 microns downstream. Several prototypes demonstrated the soundness and expected level of performance of this concept (see ref 9, section 5.1.4). However the price to pay is an extreme cleanliness in assembling the device, in order t o prevent being plagued by high voltage problems (here high voltage is only 300 volts !).
38 4.4. Forward jet tagging
Jet tagging in the forward direction opens up the possibility t o select samples of final states (Higgs boson) produced by WW or ZZ fusion, for which the signal to background ratio is more favorable than in inclusive reactions. The main acceptance region is between 7 = 2 and 77 = 4 (see figure 21), which underlines the necessity to optimize the transition near 77=3 between the “end-cap” part and the “forward” part .
”!.
PT Figure 21. Pseudorapidity distribution of forward jets,in the production of a 300 GeV Higgs boson by WW fusion.
Figure 22. Effect of pile-up on the double-tag efficiency
As an example qqH +qqWW + lvlv jet-jet was studied by simulation in ATLAS. It was shown that requiring a double tag reduces the effect of fake tags to manageable effects (-10% relative loss on double tag efficiency -El> 15GeV- due to a cell cut at 1 GeV ET), even at the nominal high luminosity. 5 . Status of Construction
5.1. Construction advancement The construction of all parts of ATLAS and CMS calorimetry is now going “full speed”. There is however a rather large spread in the present degree of completeness, as a result of several factors, including: - the amount of
R&D which had to be carried out
39 - the difficulties in transferring techniques from labs to industry - the profile of available money and man-power - the overall integration and installation plan of the experiment.
In particular the CMS cavern shall be available later than the ATLAS one, and thus installation in the pit is taking place later (in 05 and 06), with large elements being assembled in advance in the dedicated large surface hall. As an illustration the state of advance of ATLAS production is given below (table 6), for a global detector commissioning as of oct 06 . Table 6. Status of production and integration of ATLAS Calorimeters in spring 02.
ATLAS
EM-barrel EM-EC Tile HEC FCAL
Main Components procured 80% 80% 90% 90%
Module assembled 30% 25% 75% 70%
70%
40%
Integration on surface ends Apr 04 ECC July 04
Installation in pit July 04 Nov 04
ECA
March 05
Nov 04
5 . 2 . Staging plans
Being so critical for the experiment performance, and central in the installation sequence, calorimeters have been so far protected against staging or descoping plans, which may however at some stage affect some back-end electronics.
6. Calorimetry in LHCb 6.1. General strategy LHCb detection is concentrated in a 250 mrad half-angle forward cone around the beam axis (77 >2), which optimises the ratio of event rate t o coverage for B physicsz2. The aim is to have at the collision point a luminosity which maximises the number of bunch crossings with a single proton-proton inelastic interaction. In order to go fully in the direction of "clean events", the calorimeter pulse shaping/clipping is made such that signals generated by collisions in the preceding or the following bunch crossings, are negligible at the time of the main bunch crossing. The experiment aims also at using B decay modes with n-' and qo + yy in the final state. 6 . 2 . LHCb layout The LHCb calorimeter system consists of
40
- A scintillator pad detector (6000 pads) - A preshower detector (scintillator pads after 3x0 of lead)
- A "shashlik" EM calorimeter (6000 towers) - An ATLAS like "Tile" hadronic calorimeter (1500 towers)
6.3. Some performances
The energy range of the calorimeters is limited to E 300 GeV and can be covered by a single electronics gain of 12 bits dynamic. EM calorimeter and pad/preshower cells have a transverse size of 4x4 cm in the central part, 8x8 cm in the middle part, and 16x16 cm in the outer part, giving a total transverse size of about 6.5x6.5m. All devices are read out by photomultipliers (multi anodes for the pad and preshower detectors). The pion/electron rejection provided by the pad-preshower system is around 12 between 10 and 50 GeV. This complements the rejection from the combined magnetic and calorimetric energy measurements (E/p). Expected energy resolutions are l O % O / a and 8 0 % / a for the EM and hadronic part respectively. 6.4. A
WOTTY:
scintillator damage by radiations
The central part of the calorimeter will see doses, integrated over several years of running, in the Mrad range (several lo4 Gy), which will induce light losses. It was estimated that residuals in the correction of this effect will lead to an increase of the constant term of the EM energy resolution from 0.5% to 1.5%. If things go to the worse, the central part could be replaced after some running time.
7. Calorimetry in ALICE The Alice experiment at the LHC is dedicated to ion-ion and proton-ion collisions23. 7.1. Photons at large angle
The EM PHOS ~ a l o r i m e t e ris~optimised ~ to measure direct photons, 7ro and qo between 0.5 and 10 GeV/c. Since only single spectra and correlations are looked for, a complete coverage is not mandatory. The chosen detector covers looo in azimuth and f 0.12 in rapidity. It is located at 4.6m from the beam axis. Alice chose PbW04 crystals, used in a very similar way to CMS. Crystals have a transverse size of 22x22mm and are read out by APDs. In total, there are 17280 crystals in the detector.
41
7.2. Z e n , degree calorimeters Zero degree calorimeters play the special role, in heavy ion collisions, of detecting neutrons and protons from nuclear break-up of the incident ions. In a symmetric machine like LHC, the neutron spot has a 1 cmz size, in between the two rings, 120 m away from the interaction point. Protons are bent away by the beam elements and fall on either side of the beam pipes. In these conditions, compactness and radiation resistance are the prime requirements. Alice has chosen quartz fibres embedded in a Tantalum matrix for neutrons, and in a brass matrix for protonsz5. These detectors are extrapolation of what was used in the heavy ion experiment NA50 at the CERN SPS where an energy resolution of 5.4% was observed when sending 33 TeV lead ions in a similar calorimeter. 8 . Summary
0
0
In many-if not all-cases ATLAS and CMS made different calorimetry choices: this is a safety for the LHC physics programme. Monte Carlo tools (not discussed) are essential in the design phase. While EM simulations give satisfactory results, hadronic packages (GEANT4) still need improvements before being usable for LHC physics. Electromagnetic calorimeters are detectors difficult to build: high precision, high granularity has a technical cost. Located downstream of tracking devices, calorimeters suffer from the associated material: attempts being made to combine information from both detectors (converted photons, energy flow,..) need to be pursued. With the construction now in full swing, calorimeter teams are making every effort t o stay on schedule. Still, they have to stay prepared for unexpected problems, both technical and financial.. .
Acknowledgements All what was presented comes from the hard work of several hundreds of physicists, engineers and technical staff engaged since years in LHC calorimeters development and construction. They deserve warm thanks. To prepare the talk I benefited of discussions and information from many colleagues, and in particular Ph. Bloch, F. Gianotti, D. Green, P. Loch, C. Seez and L. Serin. Finally I would like to thank the organisers of CALOR2002 for a well balanced program and many extremely interesting presentations. Without the help of C. Bourge and C. Drouet, writing these proceedings (almost) in time would not have been possible: many thanks.
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References 1. ATLAS Liquid Argon Calorimeter Technical Design Report CERN/LHCC/96-41 dec 1996 2. ATLAS Calorimeter Performance Technical Design Report CERN/LHCC/96-40 dec 1996 3. Performance of a large scale prototype of the ATLAS accordion electromagnetic calorimeter. D.M. Gingrich et al., NIM A364(1995)290. 4. Performance of the ATLAS Electromagnetic Calorimeter barrel module 0. To be submitted to NIM. Performance of the ATLAS Electromagnetic Calorimeter end-cap module 0. To be submitted t o NIM. 5. CMS electromagnetic Calorimeter Technical Design Report CERN/LHCC/97-33 dec 1997 6. The lead Tungstate Electromagnetic Calorimeter for CMS. R.Brown in Proceedings of CALOR 2000. Frascati Physics series number 21, 2001. 7. CMS Note 2001/034 and C. Seez, private communication. 8. ATLAS Inner Detector Technical Design Report CERN/LHCC/97-16 apr 1997, and updates. 9. ATLAS Detector and Physics Performance Technical Design Report CERN/LHCC/99-14 may 1999, Vol I. 10. CMS ECAL calibration Strategy. Imperial College workshop, Jan 2002. 11. G.Unal for the NA48 Collaboration, in Proceedings of the 9th International Conference on Calorimetry, CALOR2000, Frascati Physics series, Vol 21,2001. 12. LHCC - March 2002 13. P. Paganini. Zero suppression in CMS. Presentation to this Conference. 14. CMS hadron Calorimeter Technical Design Report CERN/LHCC/97-31 june 1997 15. ATLAS Tile Calorimeter Technical Design Report CERN/LHCC/96-42 dec 1996 16. Studies of the response of the prototype CMS hadron Calorimeter. V.V. Abramonov et al, NIMA 457, 475 (2001) 17. Results of a new combined test of an EM Liquid argon calorimeter with a hadronic scintillating tile calorimeter.ATLAS Collaboration.S.Akhmadalievet a1 NIMA 449, 461 (2000) 18. D.Green Energy Flow in CMS (Sept 2001) and private communication. 19. ATLAS Detector and Physics Performance Technical Design Report CERN/LHCC/99-14 may 1999, Vol I1 20. Test beam of CMS quartz fibre prototype. N. Akchurin et a1 NIM A409 (1998) 593-597. Status of CMS HF Quartz Fiber Calorimetry. Y. Onel. Presentation to this conference. 21. Forward Tagging and Jet Veto studies for Higgs events produced via Vector Boson Fusion. V. Cavasinni et al. ATLAS-PHYS-2002-008 22. LHCb Technical Proposal CERN/LHCC/98-4 23. ALICE Technical Proposal CERN/LHCC/95-71 24. ALICE PHOS Technical Design Report CERN/LHCC/99-4 25. ALICE ZDC Technical Design Report CERN/LHCC/99-5
CALORIMETRY IN ASTROPHYSICS
SIMON P. SWORDY Enrico Fermi Institute, Dept. of Physics, Dept. of Astronomy and Astrophysics University of Chicago, Chicago I L 60637, USA E-mai1:
[email protected] Astrophysical environments produce charged particles and photons over an enormous range of energies. Single particles have been detected with energies in excess of 1OZ0eV. Studying these particles and photons requires a range of calorimetry techniques which are matched to the intensities and shower properties at various energies. At lower energies where the particle intensity is large, straight-forward techniques can be used on spacecraft or high altitude balloons. At the highest energies, the atmosphere itself is used as a n interaction medium because of the huge effective collecting area required. Weakly interacting particles require low background detectors with even larger mass. Experiments are underway t o use deep water volumes, the Antarctic ice, and even the Moon for neutrino detection.
1. Introduction
This review is intended to examine some of the key ideas and design considerations in making measurements of particles and photons from space. It is limited by necessity (and author expertise!) to the kinds of calorimetry which are familiar in the world of high energy physics. There is therefore no discussion here of the astrophysical techniques and detectors which probably more deserve the label ‘calorimetry’, as defined in any undergraduate text in the chapter(s) on thermodynamics. These other, more traditional, calorimetric techniques which have provided exquisite measurements of the microwave background and produced eV level energy resolution for single x-ray photons are not discussed here. A detector for high energy particles or photons placed above the atmosphere will see a constant bombardment of near isotropic radiation from space. Most particles are protons with an intensity 10-100 times that of cosmic ray muons at the Earth’s surface. Essentially all particles and photons above several GeV have their origins outside the solar system and thus truly deserve the name promoted by Compton of ‘Cosmic Radiation’. These cosmic rays consist of all stable particles and nuclei with abundances varying in a similar way to the overall abundance of matter in our galaxy. The differences between cosmic ray
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44 abundances and those observed in our galaxy by other methods have provided some of the crucial insights into cosmic ray origin. Reliable measurements of cosmic ray elemental adundances at high energy remains a central scientific goal in astrophysics. Photons and electrons are rare in cosmic rays of the same energy. However they are extremely important: In the case of photons, they are not deflected by the magnetic fields of the galaxy and therefore can be traced back to their sources. This has lead to the discovery that many photons above lGeV originate outside our galaxy - in the case of gamma-ray bursts from distant objects, apparently at large redshiftsl . The dominant feature of arriving cosmic rays is shown in Figure 12. Measurements of overall particle ‘fluxes’ are given as a function of total particle energy. These decline as a power law in energy, E-“ with an index CY 2.7 - 3.0. The only features in this spectrum are the slight steepening or ‘knee’ near 1015eV and the flattening or ‘ankle’ near 101’eV. In principle a calorimeter could be built to cover a large part of this energy range, since the depth of hadronic shower maximum increases logarithmically with energy. As shown in Figure 1 this might be expected to get up to 611 at the highest energies. The real issue is how large an acceptance aperture is needed for devices at high energy. The steeply falling energy spectrum means something in the detection scheme has to get 50-100 times larger for every decade increase in particle energy to achieve the same count rate. The extremely low fluxes at high energy can only be sampled using huge, naturally occurring, media such as the atmosphere. While most measurements below 1014eV are made above the atmosphere, at higher energies detection techniques are based on observations of air showers. The situation with photons is similar: most sources exhibit power law flux spectra. Here the energy ‘break’ for techniques is at lower energy but is more pronounced. Current/past satellite experiments have little sensitivity above 30GeV and the atmospheric techniques begin to have sensitivity above 75GeV; there is no real overlap region.
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2. Direct Measurements In the region below the ‘knee’ direct measurements are made with thin hadronic calorimeters. These are devices which because of weight constraints do not fully contain the hadronic shower. Instead they focus on collecting the energy from r 0 s created in the first interaction. Typically these instruments will contain a primary ‘target’ layer of 0.511 of low atomic number material followed by an electromagnetic calorimeter layer consisting of 15-20 r.1. of high atomic number material. A typical overall depth for these instruments is 211 with an rms energy resolution of 50%. The JACEE detectors with this design, flown on high altitude balloons, use a passive detector system consisting of
-
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-
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-
-
-
Ankle (1 particle per km2-year) tmax 6A
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(Swordy -U Chicago)
Figure 1. The overall energy spectrum of cosmic rays. The approximate intensity rates and locations of hadronic shower max. in an iron calorimeter are shown for some representative energies.
emulsion layers and x-ray films which are analyzed after the flight3. A general issue which arises with this kind of instrument is finding an adequate system to identify the nuclear charge before the interaction. As mentioned previously, a crucial aspect of cosmic ray science is the reliable identification of the elemental abundances. In principle this is a straightfor-
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ward measurement since the particle energy loss before the first interaction is c( Z 2 ,where Z is the nuclear charge. However there can be a large background produced in the ionization detector caused by albedo particles from the subsequent calorimeter shower. This could make, for example, a proton appear to be a helium nucleus, or worse. Two methods have been developed to avoid this problem in electronic detectors. A highly pixellated ionization loss detector can reject background from all regions except very close to the particle path. This method is implemented in the silicon detector scheme of ATIC4, which had its first high altitude balloon flight around Antarctica in Winter 2000/2001. ATIC uses BGO crystals for the e/m calorimeter layers to measure particle energy. Another scheme, which uses timing in fast scintillators is being implemented in the CREAM5 experiment. Here nanosecond level timing is used to separate the incoming particle arrival from subsequent albedo particles. This experiment is planned to be flown around Antarctica in Winter 2003/2004 and uses scintillating fiber/tungsten sandwiches for the e/m calorimeter section. A key issue with these experiments is the calculation of instrument response. There are no calibration beams available which can cover the range of incoming particle energies and nuclear masses so high energy response is calculated using simulations which fit with lower energy data. The direct detection of gamma-rays above the atmosphere has produced a wealth of information about the non-thermal parts of our universe. At high energies these activities were revolutionized by EGRET' on CGRO which used tracking chambers to detect the initial electron-positron pair produced by the incoming gamma-ray. This was combined with a NaI crystal calorimeter, 8 radiation lengths deep, to measure the gamma-ray energies. The next step in direct observations at high energies will be GLAST7, which uses silicon strip trackers and a CsI calorimeter to produce a much wider field-of-view instrument.
3. Effects of Energy Resolution The measurement of cosmic ray or photon spectra is clearly directly affected by the calibration of the energy scale of these devices. What is sometimes not so well appreciated is that the energy resolution can have dramatic effects on the measured fluxes. Figure 2 shows schematically the effect of instrumental resolution on measurements of the overall cosmic ray spectrum as dashed lines. The absolute size of these effects is greatly exaggerated in these examples. The effect of constant energy resolution in a / E has a direct impact on the absolute flux, this is the leftmost example in the picture. The overall measured flux is larger
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Figure 2. The effect of energy resolution on measurements of cosmic rays. The dashed lines shows examples of measured spectra under conditions described in the text
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than the actual flux at some energy by a factor 2 x a l E because of the finite resolution of the detector. More problematic are energy resolution functions which vary with energy. As shown in the center example, an energy resolution ( a / E )which improves with energy will produce a measured spectrum which is
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steeper than the original. The rightmost example shows how a degradation of resolution with energy will flatten the measured spectrum. Understanding the energy resolution function is a crucial part of any cosmic ray experiment, since it is needed to transform these measured spectra back to the input spectrum of particles. In particular, devices with resolution ”tails” to the high energy side can prove to be useless because these resolution effects cannot be reliably corrected. 4. Atmospheric Calorimetry
For the highest energy particles and photons a large collecting area is required. The atmosphere has been used extensively since the 1950s for this purpose. The vertical depth of the atmosphere near sea level is 1000g/cm2, which is around 27 radiation lengths or 1111. Curiously this is a pretty good match to the highest energies shown in Figure 1, since a cosmic ray at 1OZ0eV produces a vertical shower which maximizes at -750g/cm2. There are several techniques which are used widely for atmospheric calorimetry:
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Detection of particles at ground level. Detection of Cherenkov light from the particles in the shower. Detection of air fluorescence emission from the shower particles.
4.1. Particle Sampling The most straightforward technique for the detection of air showers involves distributing an array of particle counters at ground level to make multiple single-point samplings of the particle distributions in the showers. The electrons and muons produced in these showers range over distances of hundreds of meters to many kilometers depending on the incident cosmic ray energy and the atmospheric depth of observation. The shower particles in the shower arrive very closely in time (< 100ns) producing a strong shower ‘front’. The number of particles detected in each counter can be used to fit the shower arrival direction parameters and size. The details of the lateral distribution of particles can be used to estimate the ‘age’ of the shower or where the likely shower maximum occurred in the atmosphere. This is important because both the location of shower maximum and the shower size are affected by the initial cosmic ray energy and the nuclear mass. This can be broadly understood in a simple superposition model where the energy is spread evenly between the nucleons. The overall shower can be thought of as the superposition of A independent showers produced by the nucleons each carrying 1/A of the total energy. The overall shower size is similar for nuclei of the same energy but
49
the location of shower maximum is higher in the atmosphere for heavier nuclei since these showers look like the sum of A smaller showers. More recent air shower arrays of this type take many samples of the particles at ground level for each shower8. The KASCADE array even makes an additional measurement of the energetic particles in the shower core using a hadronic calorimeter located on the groundg. 4.2. Cherenkov Detection
During dark moonless nights air-showers are visible from the Cherenkov radiation emitted by high energy electrons in the showers. This radiation is beamed in the direction of the shower providing a fairly bright light signal from only a few thousand shower particles. This beaming makes a low energy detection threshold feasible. The pool of light on the ground has a typical radius of 100-200m which is produced by the intrinsic Cherenkov angle and multiple scattering contributions to the particle directions in the showers. The Cherenkov radiation from a shower can be fit to density distributions in much the same ways as particle distributions to get the locations of shower maximum and shower size. In some sense Cherenkov observations are more truly 'calorimetric' since they contain contributions from the entire shower not just a single plane at ground level. The overall size signal from Cherenkov observations has generally smaller fluctuations at a given energy than particle sampling. But setting an absolute energy scale is considerably more difficult for Cherenkov observations where optical collection efficiencies and atmospheric transmissions need to be well known. The most spectacular examples of Cherenkov detection are in high energy gamma-rays. Here imaging telescopes routinely detect gamma-rays at energies down to NlOOGeV from galactic and extragalactic sources. Imaging atmospheric gamma-ray telescopes, such the Whipple" 10m at Mt. Hopkins in Arizona, collect images of air showers in an -fl telescope with a few degrees field of view. A key method for providing signal to noise stems from the fact that the gamma-rays are expected from a point source whereas the background of cosmic ray events is isotropic. The gamma-ray showers that apparently come from the source have an identifiable asymmetry in the focal plane and can be separated from the more numerous cosmic ray induced air showers which have arbitrary directions. 4.3. Air Fluorescence
Fortunately nature provides scintillation light from air at wavelengths near 325nm. This radiation is emitted isotropically and therefore showers can be
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viewed from essentially any geometry with sensitive enough cameras. In a simple model of this emission the excited states of nitrogen, caused by particle ionization losses, can either decay on timescales of -100ns or lose energy via collisional quenching. Since the quenching rate increases with pressure this decrease in light yield approximately compensates for the increased ionization loss with pressure. As a result the amount of light output per unit ionizing particle pathlength in the atmosphere is nearly constant. (This is an oversimplification since the effects of temperature have not been discussed - but the net result is very similar t o this simple picture) This means that a shower viewed in air fluorescence will have an absolute luminosity which only depends on the number of particles in the shower at some depth and not on the absolute atmospheric pressure. In principle the longitudinal shower profile can be directly measured. However, the light yield is low and this technique has only been useful in the region above 1017eV. The HiRes/Fly’s Eye group in Utah have built wide field-of-view cameras with mirrors and clusters of photomultipliers for observations of air fluorescence of the highest energy cosmic rays1’. More recent observations have produced stereo views of the showers from cameras widely separated on the ground, allowing for excellent geometrical reconstruction of the events. There are also efforts to detect these events with orbiting satellite cameras which can view very large regions of the atmosphere. While the air-fluorescence technique can in principle observe huge volumes of the atmosphere, great care needs to be taken with calibration and the corrections for atmospheric attenuation. N
4.4. A i r Shower Results
Some results from atmospheric calorimetry for cosmic rays are shown in Figures 3 and 4. In the first of these (taken from PDG section on cosmic rays”) the highest energy part of the spectrum is shown multiplied by a scaling factor E3 to emphasize differences between measurements. Here the filled squares at high energies come from the ground based array AGASA and the filled circles from the HiRes/Fly’s Eye group. There are many detected particles with energies in excess of 1OZ0eV.Figure 4 shows the mean location of shower maximum in the atmosphere as a function of particle energy from a variety of experiments (taken from the PhD thesis of J. Fowler13). At lower energies these come mostly from Cherenkov experiments and above 1017eV from air fluorescence. The two model lines derived from QGSjet14 suggest the mean nuclear mass lies between protons and iron nuclei over most of this energy range.
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t I
I
I I I I l l /
I
I
I I I I l l
I
I
I I I Ill
Figure 3. Measurements of the fluxes of the highest energy cosmic rays using the atmosphere as a calorimetric volume. Taken from PDG handbook where full references appear. The experiments associated with these symbols are discussed in the text.
5. Other Techniques
The search for high energy neutrinos from astrophysical objects has produced a class of detectors which use other natural materials as the primary detection medium. Since the fluxes of high energy neutrinos from astrophysical objects are unknown the motto here is essentially ‘bigger is better’. The AMANDA15 detector has been developed using Antarctic ice as a Cherenkov radiator to provide a large mass detector. The events are viewed by strings of photomultipliers sunk into the ice. It is hoped to ultimately build a detector of size lkm3 with a billion tons of ice as the target material16. There are also groups working on deep water Cherenkov detectors17. Again, viewing Cherenkov light from showers with many photomultipliers submerged in long strings. The technical challenges for these experiments are enormous, ranging from providing photomultiplier enclosures, trigger and acquisition electronics which can survive these rough environments to understanding how to avoid luminous fish and other organisms. A crucial feature needed is the ability to separate locally produced neutrinos from cosmic ray interactions from those of astrophysical origin. This generally involves providing a method to select events which come ‘up’ through the
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Figure 4. The variation of mean location of shower maximum observed in the atmosphere by various experiments compiled by Joe Fowler. The lines show the expected values for P or Fe nuclei predicted by the QGSjet interaction model.
detector - using the mass of the Earth as a screen for cosmic rays. Interestingly a major mode of operation of these detectors is expected to be the detection of upwardly moving energetic muons produced by neutrinos in the rock mass below the detectors. So this is really moving towards using the planet as a calorimeter! There is also an effort underway to try to detect neutrinos interacting in the moon through their radio emissions'*. A large shower in a solid material produces radio waves through the Askaryan effectlg, where the shower becomes predominantly negative in solid media and the emission from the shower front is 'in-phase' which greatly enhances the radio signal for large showers. This effect has been recently detected in an experiment at SLAC2O. The idea is to view the moon through earth-based radio telescopes separated by a long baseline and look for coincidences. This is expected to be sensitive to neutrinos of energies 1020eV. N
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6. Summary The range of calorimetry in astrophysics is as broad as the phenomena being observed. Ideas about calorimeters range from small detectors for gammarays at -100MeV to schemes which start to use significant bits and pieces of our planet and even its moon. Perhaps the strongest challenge facing these huge detectors is that of energy scale calibration. Certainly the bulk of the high energy calorimetry techniques discussed here rely on extrapolations of shower physics into energy regions where no measurements exist. Progress can undoubtedly be made by combining different techniques at the same site since each can be expected to have different types of systematic errors. For example the Augerz1 experiment for ultra-high energy cosmic rays is using both ground sampling and air fluorescence measurements at the site in Argentina. This seems to be a good principle for future experiments to follow. Measurements which at first might seem redundant may be able to prcvide confidence for measuring particles in energy regions which are beyond the reach of present day accelerators. References 1. D. Reichart A p . J. 554,2001,643. 2. Compilation available at http://astroparticle.uchicago.edu/archives.htm 3. T. H. Burnett et al. A p . J. 349 (1990)25. 4. http://atic.phys.lsu.edu/aticweb/ 5. http://cosmicray.umd.edu/cream/cream.html 6. http://lheawww.gsfc.nasa.gov/docs/gamcosray/EGRET/egret.html 7. http://glast.gsfc.naa.gov/ 8. see e.g. CASA at http://hep.uchicago.edu/ covault/casa.html 9. see KASCADE at http://iklaul.fzk.de/KASCADEhome.html 10. http://egret.sao.arizona.edu/ 11. http://hires.physics.utah.edu/ 12. http://pdg.lbl.gov/ 13. J . Fowler, PhD thesis, University of Chicago, 2001. 14. N.N. Kalmykov, S.S. Ostapchenko, Yad. Fiz. 56 (1993) 105. 15. http://amanda.berkeley.edu 16. http://icecube.wisc.edu 17. see e.g. ANTARES at http://antares.in2p3.fr/ and NESTOR
at http://www.nestor .org.gr/programme/scinet-index. htm 18. P. Gorham et al. in proceedings RADHEP2000 conference, AIP 579, 2001, 177. 19. G.Askaryan, Sov. Phys. J E T P 14, 441 (1962);21, 658(1965). 20. D. Saltzberg et al. Phys. Rev. Lett. 86 (2001)2802. 21. http://www.auger.org/
CALORIMETER CONSIDERATIONS FOR A LINEAR COLLIDER DETECTOR
RAYMOND E. FREY Physics Department and Oregon Center for High Energy Physics University of Oregon, Eugene, OR 97403 E-mail: myfreyOcosmic.uoregon.edu
Current trends in the consideration of calorimeters for a future linear e+e- collider detector are discussed. The physics requirements and LC environment are briefly reviewed. The paradigm that excellent jet reconstruction can best be realized when the charged and neutral jet components are separated in the calorimeter is discussed. Design ideas are given, citing specific examples now under consideration in Europe, Asia, and N. America.
1. Introduction
A concensus has emerged internationally in the last two years that an e+elinear collider (LC) in the energy range 0.5 to 1 TeV is the highest priority future project in elementary particle physics. Accelerator designs and test facilities in Europe, N. America, and Asia have made tremendous progress. This activity has inspired increased attention to LC detector design. Here, the prevalent ideas for calorimeter design are discussed. We start by highlighting the physics prospects, then discuss the LC detector environment, followed by design considerations and specific examples. There is perhaps some feeling in the hadron collider community that e+edetectors are straightforward, given the relatively benign LC environment, and perhaps do not merit significant R&D effort. However, I argue that this environment in fact allows one to think of detectors which are significantly better than the previous generation of excellent detectors at LEP and SLC. Hence, the LC provides an opportunity to achieve improved levels of physics measurement, and we should strive to take advantage of this. Calorimeters are perhaps undergoing the most extensive evolution in design to meet the LC challenge. An important element of the design philosophy is that the goal is not to build the best possible calorimeter, but rather the best possible detector. This highlights the fundamental interdependency of the calorimeter and other sub-detectors in making a physics measurement. Our experience with previous
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detectors is pointing the way. But significant R&D will be required to take this next, significant step. And it is now underway. 2. Physics Requirements
In general, the main physics goals of the LC are the same as the LHC, namely to uncover the new physics responsible for electroweak symmetry breaking and to explore other phenomena at the TeV energy scale. Detectors must be prepared to study Higgs physics, supersymmetry (SUSY) if present, top physics, new and old gauge bosons, and so forth. While the LHC will likely be the discovery facility, the LC will be required to fully explore the physics. Perhaps one would expect scenarios similar to that of the W and 2 bosons, where discovery at hadron colliders was followed by a full exploration of their properties at LEP/SLC. So the LC is expected to make measurements which are difficult or impossible at the LHC, but are essential for the elucidation of of the underlying physics. Perhaps the most important example, and the one most pertinent to calorimeter design, is the capability to measure electroweak processes which decay hadronically. In fact, multi-jet final states are common signatures of most new physics processes, many of which involve W and 2 as intermediate states. Typical examples include the separation of the hadronic decays of WW from 22, or 22 from Z H . Some important final states, such as H H Z to determine the Higgs self-coupling, have small cross sections and hence require the reconstruction of all final states, including those with 6 or more jets. Assuming that the detectors have this capability, the LC can provide these measurements. In addition to jet final states, the LC physics also requires that leptons are well measured. Tau identification and measurement becomes very important at the LC, and is mentioned further below. SUSY final states require that the calorimeter coverage extend to small scattering angles, with no cracks. There is no clear physics case at the LC for excellent photon energy resolution, such as that for H + yy at the LHC. On the other hand, some SUSY models predict secondary vertices where a photon is the only visible particle. Thus, one would like to identify photons which do not originate from the IP.
3. The LC Environment The LC designs call for a maximum fi in the range 500 to 1000 GeV at a luminosity of a 2 - 4 ~ 1 0cm-2s-1. ~~ The ease of low energy (Mz) running is design dependent and a subject of current debate. A lovely feature of the LC is that the collision IP is indeed a point. Along with the small beam radius, this
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allows excellent vertexing capability. The main environmental issues which drive calorimeter design are IP radiation and the accelerator bunch timing structure. 3.1. The IP and IP Radiation The high charge density of the beams at the LC IP gives rise to photon radiation (beamstrahlung) and production of low energy e+e- pairs. Roughly lo5 pairs are produced per beam crossing, as shown in Figure 1. Fortunately, the pairs have small, limited transverse momentum. Therefore, the detector solenoid prevents them from entering the detector proper. To allow the vertex detector to be 1 cm from the IP, the field strength needs to be about 3 T or greater. N
Figure 1. Pair production simulation from a LC bunch crossing. Note that the x and y scales are very different - the conical masks are about 2' from the beamline.
3.2. Bunch Timing The TESLA and NLC/JLC designs have quite different timing structures. The differences are intrinsic to the linac RF technologies employed. For TESLA, bunch trains are supplied at 5 Hz. Each train has a length of 0.95 ms and the bunches cross every 337 ns. For NLC/JLC, the corresponding numbers are 150 Hz, 269 ns, and 1.4 ns. The physics event rate is small, but it is not yet clear if timing within a bunch train is required to avoid pile-up from 2-photon
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events and backgrounds. Individual bunch timing would clearly be a challenge at NLC, but should be readily achievable for the TESLA calorimeter. One notes that there are lengthy intervals between bunch trains. This implies that power cycling of calorimeter electronics could provide large reductions of the heat load. The NLC (duty cycle 5 x lop5) provides an advantage in this case compared to TESLA (5 x Finally, a small bunch crossing time interval requires a finite beam crossing angle to avoid additional unwanted bunch crossings. An angle of 20 (8) mrad is chosen for NLC (JLC). While a non-zero angle is not in principle necessary for TESLA, the zero-angle crossing design is technically difficult. A crossing angle has obvious implications for detectors placed at very small angle, but these detectors inside the masks are not discussed further here. 4. Making the Most of the Tracker: The Energy Flow Method
As discussed above, excellent jet reconstruction and measurement is the outstanding challenge for LC calorimeters. Two basic facts drive the approach to this measurement. First, jets are composed primarily of charged particles. For example, for 22 --t jets, the visible energy is 64% charged particles, 25% photons, and 11% neutral hadrons. (These numbers change very little for other hadronic final states.) Second, jet particles do not have large momenta, and the energy resolution for charged particles is vastly better in the tracker than the calorimeter. This last point is illustrated in Figure 2 which gives a typical momentum distribution, and in Figure 3 which compares tracker and calorimeter resolution for charged pions.
Trucker, SO 10-3
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Figure 2. Typical charged particle momentum distribution for a multi-jet process, in this case e+e- + 22 +jets.
Figure 3. Comparison of typical singleparticle energy resolution for charged pions for calorimetry and for an LC tracker. The tracker is the SD design with 0 M 90°.
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Clearly, one would like to take full advantage of the tracker for jet physics. In fact, this idea has been in use in e+e- detectors for ages, in one way or another. It is sometimes called “energy flow”, although there is no standard use of the term, as it is often used to describe the more far-reaching methodology discussed below. In any case, at the LC we are in position t o try t o push the energy flow idea t o a new level. Various approaches on how to achieve this are discussed in the next section. Finally, it is noted that energy flow will fail for sufficiently high fi due to higher track density and the eventual convergence of the single-particle resolution curves. Simulation studies indicate that this is well above 1 TeV. 4.1. Segmentation Requirement
Which strategy will best allow one to take advantage of the tracker measurement of the charged pions in jets? First, the photons will be measured in the electromagnetic calorimeter (ECal). So if one could make the ECal transparent to hadrons, then neglecting neutral hadrons, one would have excellent jet
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G
I
Figure 4. Illustration of the interaction of a 7ro and a .rr+ from a jet in a cartoon calorimeter. The .rr+ does not interact in the ECal in (a), but does in (b). The ECal has no longitudinal segmentation and the transverse segmentation is indicated.
59
measurements - all the energy in the ECal would be from photons. This is illustrated in Figure 4(a). (Hence, it is helpful for the ratio of radiation length to interaction length, Xo/X, to be relatively small for the ECal.) Unfortunately, a real ECal will have X 1, so our cartoon will often look like that in Figure 4(b). Without sufficient segmentation in the ECal, we cannot separate the photonic contribution(s) from that due to the pion(s). And in general, one would like to have segmentation in 3 dimensions to do this efficiently. Similarly, one needs to separate charged and neutral hadrons in the hadron calorimeter (HCal) in order to take advantage of this method. The highly segmented approach to the implementation of energy flow is the one adopted by the TESLA and the American SD designs, discussed below. Two other approaches can be considered. One might emphasize the ECal energy resolution by using crystals. Here, one has the problem with lack of segmentation illustrated in Figure 4, but would presumably try to correct using average energy depositions. CMS has shown that this is helpful'. One would presumably include small Xo/X as a design criterion. Finally, one can emphasize the hadronic response of the calorimeter by choosing one which provides hardware compensation. Charged/neutral sepa-
-
0
2
4
6
8
10 3.2
14
16
18
20
0
2
4
6
S
10
l2 14
16
18
20
Tmck€hskr distance (an ) Figure 5. Example of ECal transverse segmentation requirement for e+e- -+ tf -+ jets for the SD detector. The left-hand figure gives the transverse separation between the charged particle position determined in the ECal and the centroid of all photon showers. The righthand figure is the transverse separation between charged particles as determined by the ECal and the tracker. Figure from M. Iwasaki.
60
ration would still be necessary, and it is difficult to find a technology which combines compensation with excellent segmentation. This is the approach of the JLC and American LD detector designs. 4.2. Requirements for the Electromagnetic Calorimeter
In considering ECal segmentation, one should first examine what is implied from LC jet physics and the detector induced charged particle sagitta, which is proportional to BR2. A typical example is given in Figure 5 for the SD detector. We see that the physics requires a separation at the level of x 1 cm. Hence, we strive to use a small MoliBre radius, tungsten being an obvious choice with R, = 0.9 cm. A figure of merit is BR2/R,. Finally, the segmentation need to be comparable to R,, smaller if possible. The TESLA and SD designs implement this segmentation using silicon detectors throughout the ECal, amounting to N lo3 m2 of silicon.
/
\ ECal
\
-104
/
-80 -78
-76 -74
-72
-70
X
Figure 6. Photon “tracking” in the SD detector Si/W ECal. The small squares are hit cells. The shower profile is fit and extrapolated to the IP, shown as the dark line. The front face of the ECal is at the upper right. Based on a GEANT4 simulation. Figure from T. Abe.
61
A dense, highly segmented ECal provides other important assets. It allows tracking of MIPs to extend into the calorimeter. As we point out below, this is important for the HCal, too. It also provides photon tracking, which opens the possibility to find photons not originating from the IP, potentially a critical signature for new physics. Figure 6 shows a display from a GEANT4 study of photon tracking in the SD detector. The resolution on the extrapolation to the IP was found to be 3.5 cm in both r-4 and z for 10 GeV photons. The same study applied to charged particles found a 1 cm error. Numerous physics studies have pointed out the importance of identifying 7's. Also, because of the benefits of using the tau as a polarimeter, one might demand that the calorimeter have the ability to identify some specific decay modes. Figure 7 shows that with sufficient granularity, one of these decay modes can be identified even at very high boost.
Figure 7. Simulation of a 300 GeV T with the decay mode Si/W ECal and digital HCal. Figure from H. Videau.
T
+ pv -+
7 r T + ~ O in u
the TESLA
4.3. Requirements for the Hadmnic Calorimeter
While hadronic showers are large and diffuse, one still expects a highly segented HCal to be very important, primarily because tracking MIPs through the HCal is seen to be a key element in energy flow pattern recognition. Here is an outline of how this information might be used: One would do tracking of charged particles in the HCal. If they do not interact, they are probably muons (to be verified with a muon detection system). If a track terminates at a shower(s), begin pulling in shower energy based on a x2 shape criteria. A constraint on E / p matching would help terminate the process. Whatever is left is due to neutral hadrons (subject to reasonable consistency constraints). And one gets reasonable muon identification as part of the process.
62
-
The “digital” HCal, discussed further below, pushes the transverse segmentation to 1 cm. This approach is being pursued as an option for TESLA and with the SD detector. At this time, sharp criteria for HCal segmentation are still being developed. So it may be the case that a practical compensating technology like Pb and scintillating tiles can also provide adequate segmentation. This path is being pursued with the JLC and LD detectors. We note that all designs to date have been able to put both ECal and HCal inside the solenoid coil, even with the large fields being pursued at the LC. Of course, this is beneficial to calorimeter resolution if it can be achieved. This is aided by the fact that the HCal at the LC does not have to be nearly as deep as those at a hadron collider, perhaps even more so for highly segemented calorimeters which allow tracking of MIPS.
4.4. Limits to Jet Resolution
It is interesting to evaluate jet measurement using the energy flow teechnique in the case where the reconstruction algorithms are capable of correctly matching all energy depositions with the corresponding particle, i. e. perfect pattern recognition. Using the process e+e- -+ qq as a benchmark, Figure 8 gives a sample jet-jet mass distribution. And Figure 9 gives the jet energy resolution as a function of Ejet. The width of the peak in the mass distribution is dominated by the ECal resolution for photons ( x 0.15/&?), while the tails result from fluctuations of neutral hadrons and neutrinos.
0.5 l
Figure 8. Jet-jet mass distribution for e+e- + qq at 200 GeV in the SD detector in the limit of perfect pattern recognition.
100 .
E,.,
IGeVI 200 1
300
1
Figure 9. Jet energy resolution for e+e- -i qq as a function of Ejet in the SD detector in the limit of perfect pattern recognition.
63
The fit in Figure 9 gives a resolution of 0.15/-. This agrees with the result derived2 using a formulaic approach. The agreement demonstrates that fluctuations in particle types are unimportant, the resolution is limited by detector resolution, and QCD effects are relatively unimportant. This is in dramatic contrast to the case for hadron colliders, where detector resolution is Table 1. Parameters of calorimeter designs currently under consideration. Note that many parameters will change as designs evolve. The labels T and D refer to two TESLA design options.
Tracker type
TESLA5
SD6
TPC
Silicon
L D ~ TPC
JLC7 Jet-cell drift
ECal Rmin barrel (m) Type Sampling Active Gap (mm) Long. readouts
1.68
1.27
2.00
1.60
Si pad/W
Si pad/W
scint. tile/Pb
scint . tiIe/Pb
30 X 0.4Xo +10 x 1.2Xo
30 X 0.71Xo
2.5 (0.5 Si)
2.5 (0.3 Si)
1 (scint.)
1 (scint.)
40
X
0.71Xo
38
X
0.71Xo
40
30
10
3
Trans. seg. (cm)
X 1
0.5
5.2
4
Channels ( x lo3)
32000
50000
135
5
zmin endcap (m)
2.8
1.7
3.0
1.9
1.91
1.43
2.50
2.0
TJSrpe
T: scint. tile/SS D: digital/SS
digital
scint. tile/Pb
scint. tile/Pb
Sampling
38 x 0.12X (B), 53 x 0.12X (EC)
34 x 0.12X
120 x 0.047X
130 x 0.047X
Active Gap (mm)
T: 6.5 (5 scint.) D: 6.5 (TBD)
1 (TBD)
2 (scint.)
2 (scint.)
Longitudinal readouts
T: 9(B), 12(EC) D: 38(B), 53(EC)
34
3
4
T: 5-25 D: 1
1
19
14
5"
2O
2O
8'
3.0
2.5
3.7
3.7
4
5
3
3
option: Si pad shower max. det.
scint. strip shower max. det.(2 layer)
HCal Rmin (m) barrel
Transverse segment. (cm) Omin
endcap
coil Rmin
( 4
B (TI Comment
Shashlik ECal option in TDR discontinued
64
in fact nearly negligible3 compared to QCD and underlying event effects. The ideal result should also be compared with simulations from the TESLA group, which give jet energy resolution of a E / E = 0.30/& for e+e- + qq with realistic simulations, as shown at the previous meeting4 in this series. So presently there is a factor two between the ideal case and an existing reconstruction. Presumably, some of this difference can be reduced by the development and improvement of reconstruction algorithms. To summarize, these studies allow one to make two general points: (1) LC jet resolution will be limited by detector resolution, not by QCD or other effects not under the control of the experimenter. (Nevertheless, it is still important to quantify QCD effects, which are likely to become more important for final states with many jets.) (2) The jet resolution will be in the range (0.15 to 0.30)/& (for 2-jet final states) for the TESLA or SD type of detector (see next section). It is important that proponents of various calorimeter designs be able to compare resolutions using equivalent full simulations, eventually reinforced by test beam results. 5 . Design Ideas
Table 1 summarizes some of the major calorimeter parameters for current detector designs. It should be noted that in some cases these parameters are rapidly evolving, and are likely to soon be obsolete, if they are not already. The TESLA parameters are based on the TDR from 2001, except that the Shashlik ECal option is no longer included. In the discussion below, we note some recent changes and highlight some areas of R&D activity. The JLC parameters are based on the recent (July 2002) 3T design in the ACFA report. 5.1. TESLA
The calorimeter for TESLA consists of a highly-segmented (imaging), silicontungsten (Si/W) ECal. There are two options for the HCal, one using scintillating tile detectors and the other a “digital” HCal discussed below. Both HCal options use the same mechanical layout. The barrel ECal consists of eight modules, a few of which can be seen in the figure. In the design from the TDR5, the ECal front end electronics is at the edges of each module, positioned to be out sight of the IP. The readout end of the detector slab is shown in Figure 11. Recently, an alternative design has been developed which inserts the front end electronics within the slab. This has several advantages’, but requires more attention to thermal management. Cost is always a concern for silicon detectors. In the TESLA TDR, the silicon detectors are about 70% of the ECal cost While the TDR design included 40 Si layers, an alternative design
65
Figure 10. Simulated event in the TESLA detector with the digital HCal option.
with coarser sampling (20 layers) would reduce expense with a corresponding increase in photon resolution (0.11 to 0 . 1 4 / a ) . A conservative estimate of the cost in 2005-10 for these relatively simple silicon detectors is $2/cm2. This puts the ECal cost estimate at roughly 70 MEuros for the 20-layer design. The tile HCal option was discussed in detail by Korbelg at this meeting. The digital HCal option calls for enough segmentation so that a one bit readout suffices. This offers the possibilty of a greatly simplified readout which can offset the cost of the increased segmentation. The current design calls for 1 cm transverse segmentation. Figure 12 compares single particle resolution for the usual analog sum of HCal cells t o the “digital” sum, that is, the multiplicity of hit cells. We see that the digital resolution is actually slightly better than that for the analog sum. An R&D effort is underway to choose an appropriate detector for this option. RPC detectors, if made to operate reliably, might be a good choice. A glass RPC, being considered for TESLA, is shown in Figure 13.
66
m ax45 m m l;lontmd ekbmjcs Figure 11. The end of the Si/W detector slab from the TESLA TDR design.
qo5
w a
0A
03
02
01 0
2
4
6
8 1 0 1 2
lxdmnenergy GeV Figure 12. Comparison of single hadron energy resolution for a sum of the full energy of hit cells (triangles) and the digital sum (squares). The circles are after additional pattern recognition is applied to the digital hits. Figure from H. Videau.
67
Figure 13. A glass RPC being considered for the TESLA digital HCal option. Figure from V. Amassov.
5.2. JLC Detector
The ACFA/ JLC detector is based on a hardware compensating configuration of P b and scintillating tile layers in the ratio 4:l. This structure has already undergone extensive test beam evaluation, an example of which is given in Figure 14. One challenge for this design is whether the segmentation, both
O p t k a l F h ~ ~ ~ f UEM X iC
(O.7mm
resolution vs. Pb thickness for n I
h
K v W 7
.
I
'
I
'
I
x144)
'
fit function J(u:+dXu:)
60
2
U.(Z) u,(Z rnm-'") 25.lf0.9 1 l . l f 0.2 25.6f 1.3 8.5f 0.4
!-4GeV 1 GeV
/
4
50
tphotnn
40
..
3c
1 CI"
I ZOSV
Jc." ...
0 '00"
2c
I
1
.
,
.
,
.
3 4 6 b thickness J d (rnrn"
Figure 14. Test beam energy resolution for pions for the JLC Pb/scintillator configuration.
Figure 15. Pixelated photon detector being developed to readout the fibers from the JLC calorimeter scintillators. Figure from Y. Fujii.
68
transverse and longitudinal, is sufficient, especially for the ECal. To aid spatial separation, a shower maximum detector is foreseen, consisting of one x and one y layer of scintillating strips. Another challenge is the readout of the light from the scintillator, which is only 1 mm thick in the ECal. Hence, the photon detectors must have high gain, but be formatted to read out thousands of channels. Hence, the R&D for these devices is critical. Figure 15 shows a CCD-based device under investigation. 5.3. SD and LD
The SD detector being considered in N. America is a larger version of a detector first proposed at Snowmass 19961°. The calorimeter for the current SD detector is similar to the TESLA design. It has a Si/W ECal and a digital HCal. The ECal R&D is currently focussed" on the issue of how to integrate detectors and electronics. A single readout chip mounted on a silicon wafer of pads would effectively reduce the readout channel count by a factor lo3. This is sketched in Figure 16. A simple cooling scheme may be possible if one uses power cycling to reduce the heat load by a factor lo3.
-
-
n n
Figure 16. Center of a silicon detector wafer with 1000-channel readout chip bump bonded to the detector array. The detector pixels are hexagonal cells 5 mm across. A few representative signal traces are indicated.
Figure 17. A schematic of a section of a gas electron multiplier (GEM) being considered for the SD digital HCal. Figure from A. White.
The SD digital HCal effort is investigating three different detector options: RPCs, GEMS, and extruded scintillator tiles. The goal for each is to provide 1 cm segmentation at reasonable cost. The simple electronics possible with these technologies makes them compatible with the digital scheme. A GEM
69 schematic is shown in Figure 17. The LD calorimeter closely resembles the JLC detector. It exists as a configuration file for simulation studies, but currently no attempt has been made to provide a realistic design.
6. Prospects Calorimeters are being designed to take full advantage of the wonderful detector environment at an LC. The most important criteria are based on detectorwide measurements, such as jet reconstruction. This is an interesting time in this development: There are new ideas to implement, test, and compare with alternatives. The energy flow methods are not simple to test, since to work well they require a full set of pattern recognition and reconstruction tools. Test beam measurements will be required to compare with full simulation results. R&D is required to answer both basic and detailed questions. We do not know now what the new physics will be at the LC, but hopefully the choices being made now will improve the discovery reach!
Acknowledgements This work is supported in part by the US Department of Energy under award DE-FG02-96ER40969.
References 1. 2. 3. 4. 5. 6.
7. 8. 9. 10. 11.
S. Kunori, these proceedings. V. Morgunov, these proceedings. D. Green, these proceedings. H. Videau, Proc. Calor 2000, http://wwwlapp.in2p3.fr/Calor2OOO/. The TESLA TDR, http://tesla.desy.de/new-pages/TDR-CD/start.html, DESY, March 2001. The American Linear Collider Working Group, “Resource Book for Snowmass 2001, Part IV,” hep-ex/0106058, 2001. ACFA LC Working Group Report, http://acfahep.kek.jp/acfareport/. H. Videau, these proceedings. V. Korbel, these proceedings. C. Damerell, et al., pg. 431, and J. Brau, et al., pg. 437, Proc. Snowmass 1996, www.slac.stanford.edu. R. Frey, these proceedings.
CALORIMETRY DESIGN WITH ENERGY-FLOW CONCEPT (IMAGING DETECTOR FOR HIGH-ENERGY PHYSICS)
V. L. MORGUNOV DESY, TESLA-FLC, Notkestrasse 85, 0-22603Hamburg, Germany E-mail:
[email protected] Permanent address: ITEP, B. Cheremushkinskaya, 25, Moscow 11 7218, Russia
The Energy-Flow method is based on the idea to replace, for the charged fraction of the event, the energy and angle information as derived by the calorimeter by the much more accurate particle momentum as measured in the powerful tracker device. The optimal application of this method requires establishment of sufficient spatial and energy resolution for all individual tracks to allow efficient shower separation in the boosted jets. Thus the calorimeter has to have good energy resolution and it has to be highly granular. The imaging detector capability, along with the use of the Combined Energy-Flow technique, allows the reconstruction of almost all individual particles in an event. Reconstruction for di-jets from 2’ decay using the Combined Energy-Flow method within TESLA detector results in a final mass resolution of better then 3 GeV.
1. Introduction
The Energy-Flow notation originally used to describe the energy flux inside the developing QCD processes in the physical chain: Partons ( e + e - + qq or W+W- or Zoh or so ...) + Fragmentation (hard processes =+ partons + strings) + Hadronization (soft processes + . . . sea quarks) + Particles at the interaction point ( B , D, ..., Ao, ..., no,n*,p , ... ). The backward problems for this chain have been more or less successfully solved by jet finder algorithms (Cone, JADE, Durham, Cambridge, kt, ...), by means of heavy flavour tagging and with the modern methods of event analysis, assuming that the four-momenta of all particles at the IP are known, and all vertex positions have been reconstructed. This concept is not the subject of this article. The LEP experiments introduced so called Energy-Flow techniques (methods) in 1994-1995ll2 to get better jet energy resolution by taking into account tracker information, partially replacing the calorimeter information. This resulted in reconstruction of “pseudo-particles” (E-flow objects). The recon-
+
70
71
struction of individual particles (charged or neutral) in LEP detectors was very difficult because of coarse calorimeter granularity , lack of or small magnetic field, lack of longitudinal segmentation, and additional dead material in front of or inside the calorimeter. The Energy-Flow technique has been improved by modern experiments such as CDF3, H I 4, ZEUS5, and it will also be used in CMS‘ and ATLAS7. The conventional calorimeters was tuned to get the best energy resolution for single particle and it does not work well with the number of particles (jet) that impact with such a calorimeter. The jet energy resolution of any existing detector is not better then 9 0 % / ~ 1 9 ~ 6if ~it 1is 0not used the Energy-Flow method; and it is near by 50-60%/&11J2J3>7 if used. The current evolution of this concept leads us to a new definition of EnergyFlow, different from the original concept. The next generation of HEP detectors and calorimeters can be built in such a way that it will be possible to reconstruct four-vectors of almost all particles (charged and neutral) in an event by means of a new Combined Energy-Flow method. An example of a new HEP detector14 is the imaging detector for the next generation of accelerators, that hopefully will be the e+e- Linear Collider (LC) at an energy region of ECM = 90 - 800 GeV. The TESLA detector has a typical collider detector architecture. Close to the beampipe a high precision vertex detector is installed. It is surrounded by tracking system consisting of Si detectors and large volume TPC. The electromagnetic and hadronic calorimeters sit outside the trackers. The complete assembly is immersed into a solenoidal magnetic field of 3-4 Tesla. The LC has “clean” events: there is no event overlapping - low event rate, clean environment - small background, possible constraint to the beam energy. The detector at an LC will not have an event trigger at all. So, the detector will work similar to a bubble chamber. A long time ago it was understood that the di-jets mass resolution is not a simple problem. The reason for this is the overlapping showers of particles in the jet. “Clearly how to handle the jet-jet resolution problem is one of the lessons being learned right now at LEP2 and is more dificult than most people imagined. This is a reason for the emphasis o n better energy-flow tool for LC detector. ” /Conceptual Design Report, 1997, ECFA-DESY/. Many physical tasks for the LC exist that require the best di-jet mass resolution, such as the mass reconstruction and separation for hadronic decay modes. A partial list of reference reactions for the World-Wide LC Study15 is shown here: 0 Measurement of MW from jets, without using the beam-energy con-
72
Tracker and Calorimeter Resolution in Absolute Scale
10
1
10
10
-1
-2
1
10
lo2
Energy (GeV) andhlomentum (Ge V/c). Figure 1. Th e main reason t o use tracker for event/jet energy measurement together with calorimeter is the very good momentum resolution - that is much better then calorimeter energy resolution in the wide energy region. T h e hadron calorimeter resolution of 50 32 %, and electromagnetic calorimeter of 10 % resolution are shown, together with two TPC momentum resolutions.
straint; 0 W / Z separation by mass in hadronic decay modes. 0 Measurement of Mt from jets, without using the beam-energy constraint; 4- and 6-jet reconstruction of e+e- + tf events. 0 Measurement in e+e- + Z h of branching ratios for h decay to bb, cC, T+T-, gg, (or WW and 22). Measurement of Higgs self coupling in e+e- + Zhh. 0 Measurement of t f h coupling cross section for e+e- -+ tfh. All of these reactions require di-jet mass and jet energy resolution of about 30% / fior better. Such a difficult requirements lead t o new reconstruction methods and in turn to the new requirements for the detector properties and to new detector design. The task of this article is to introduce the new Combined Energy-Flow concept and to explain a new path to detector design that takes into account new imaging reconstruction methods from the very beginning.
73
Figure 2. The Combined Energy-Flow technique for the imaging detector uses a priori knowledge for the showers separation and substitution.
2. Combined Energy-Flow, Main Idea
The main idea and resulting benefit of Combined Energy-Flow is based on two rather general and well known statements: 0 The well-measured particle momentum substitutes the nearly random energy spread in the imaging calorimeter volume (see Figure 1). This leads t o a decrease of the energy fluctuations in general. 0 Vector subtraction of overlapped showers is more effective in comparison with scalar subtraction due to the utilization of the momentum vector. The additional constraints decrease any fluctuations. Figure 2, which shows a sketch of two charged particles overlapping with one neutral, can be used to illustrate this statement. If the momenta of charged particles are known one can collect the detector hits along the predicted direction and substitute the collected cluster energy with the well measured momentum of its origin. When doing this, the vector character and the bending of the charged particles in the magnetic field is taken into account. The rest of the detector hits are attributed to and measure the energy of neutral particle - treated by the usual cluster algorithm. Such a technique requires an imaging reconstruction methods. This implies that the
74
calorimeter must be constructed as a high-granularity imaging calorimeter. The difference between an old LEP-Energy-Flow method and the new one is that the Combined Energy-Flow is not trying to reconstruct the jets but it aspires for the separation and substitution of all charged particle showers, using a priori knowledge of their momentum. The fine-granularity imaging calorimeter helps to reconstruct also the neutral part of the event carefully. Finally this allows to reconstruct every particle at the interaction point. After such a procedure any of the existing jet finders can be applied to analyze the event. The details and strict mathematical definition of the reconstruction problem can be found in the appendix of Snowmass2002 proceedings16. Now let us look at the promise of this concept.
3. Combined Energy-Flow, Energy Resolution Limit for the jet/event which has negligible showers overlapping: If every particle in the event can be distinguished separately: 60 % of all energy will be measured with the tracker precision; 30 % of the energy will be measured with the rather good resolution of the electromagnetic part of the imaging calorimeter; only about of 10% of the energy will be measured with the hadron calorimeter with relatively poor resolution. The numbers illustrating this are shown in Table 1. One can estimate the combined resolution as:
Table 1. Energy resolution Energy fraction for e+e- + hadrons ECM = 90 - 800 Gel/
Measured Tracker ECAL HCAL
Charged particles Gammas Neutral hadrons
Ech.hadr M
Energy resolution
0.6 ' E
ffch.hadr
ET x 0.3. E Eneut.hadr
ffcomb = Jff%.hadr
ff7
0.1 ' E
un.hadr
10-4E2h.pa~t
x 0.11-
o . 4 G
+ ff; + ffieut.hadr
After substitution one has: ffcomb =
J(0.6)4
X
+
(10-4)2E4 0.3
X
+
(0.11)2E 0.1
X
(0.4)2E
with the lower limit of the energy resolution as: !%Z@ x
E
J ( E x 3.6 x 10-5)2 + (0.14/&)
2
+
0.14/&
75
A more general formula for the energy resolution, taking into account the constant terms U y = 0.12 0.005 E y ; Uneut.hadr = 0.4 0.05 Eneut.hadr leads to the same limit numerically:
JC
+
z)2(
+(
ucomb
(3.6 10-5 x E ) ~
E
+
T)2 0.038
+ (0.005)2 + 0.14/&
Thus, the lowest limit of energy resolution for a jet or whole event is about 14% so far unreachable by any calorimeter.
a,
35
...............................................
30
......,.............................................
25
......,.
..........
I , , , I
20 15
...... .........
10
......,. ........
I
-
.
.-
5 0
8..
...... - - - - - - - -,- -
0
:
a?,
20
40
60
80 100 I20 ZO mass (GeV)
Figure 3. Full simulation result for TESLA detector with SNARK reconstruction program. (2' mass width for this sample was set t o 100 MeV, to show the detector resolution only).
Figure 3 shows the mass resolution for ZO at its resonant energy; in this case the mass and energy of the event is the same parameter. The distribution in Figure 3 is not the scalar energy sum; but it is the sum of reconstructed particle four-vectors at the IP. The shape of the distribution is not Gaussian due t o the mixing of many different event geometries, with very different degree of shower overlap. In some events all particle showers were reconstructed separately and the energy resolution approaches the theoretical limit. That is visible as the narrow peak over the Gaussian distribution with an effective sigma of about 30 % over
a.
76
4. Combined Energy-Flow, Reconstruction Algorithm
Let us look in a bit more detail, but briefly a , at the reconstruction algorithm for a better understanding of the requirements for the imaging detector design that follows from the Combined Energy-Flow concept. The cluster search procedure for charged tracks in the imaging calorimeter starts from the predicted point and direction of the track at the imaging calorimeter “face” (see Figure 4).
HCAL
Figure 4.
Combined Energy-Flow algorithm in the reconstruction program SNARK.
For example, one builds a helix from the impact point at the imaging calorimeter face, and collect the hits along this curve - track core. Then one can build the first hypothesis for the collected cluster. If all hit’s amplitudes are near the MIP value so one can define the track as a muon. In this case one has to stop the collection, calculate properties and probability and remove hits from further analysis. If it is not a muon, one can check the next hypothesis - an electron. Again as an example, for the particular ECAL structure of a Si-W imaging calorimeter with 1 by 1 cm cell sizes, half of an input energy is collected in the cylinder of one cell size radius around the helix prediction. This can be shown in the separate simulation of such electromagnetic showers. Then one can take the next shell around the core - and so on and so on, up to the track energy and taking into account the ECAL energy resolution. At each step the 3-d ~
aThe algorithm for hypothesis building includes 35 logical branches for now.
77
electromagnetic hypothesis is built and compared with the collected cluster shape. The collection stops when the collected energy and cluster shape are agree with the prediction. If the collected cluster is not valid for the muon or electron hypotheses (both of them are much better defined in comparison with the hadron one) it is classified as a hadron. The fitting and collecting procedure for the hadron cluster is close to the electromagnetic one, however the expected shower shape and fluctuations are taken from a simulation of appropriate hadronic shower. All collected hits with well defined hypothesis are excluded from further examination. The cases of the overlapped showers treated at the separate algorithm branches with some additional conditions and bit collection procedures that include hit weighting depends on the input particle energy. One hit after such a procedure can be member of different clusters, or even it can go to the residual of the hits, that means it will belongs to some neutral cluster partially. The good quality building of the hypothesis for the collected cluster requires the high granularity mostly for the the electromagnetic part of imaging calorimeter. The rest of the hits after the charged track procedure is finished may go to the more or less usual clustering procedure that should resolve the overlapped gamma-showers. Again this leads to the fine granularity of the the electromagnetic part of imaging calorimeter. 5. From IP to Calorimeter in detail We will start from the requirements for the tracker, as it plays a significant role in the Combined Energy-Flow technique. Particles are propagated from the IP to the imaging calorimeter face through the relatively small amount of matter in a large magnetic field with possible decay, nuclear interaction, or gamma conversion. Charged tracks with Pt < 0.76 GeV/c in a 3 Tesla magnetic field will never reach the imaging calorimeter barrel surface. The big amount of low energy curling tracks in event leads to additional requirements for the tracker reconstruction procedure. The bending of charged tracks in the large magnetic field (?~p # ?fa,,) leads to a significant shift of the position of the jet center of gravity in the calorimeter volume in comparison with zero or small magnetic field. It leads in turn to the deterioration of jet energy and di-jet mass resolution because of the angular dependences. Any tracker reconstruction error leads t o the bad reconstruction of the particular shower and rather often to the hits doublecounting.
78
+ t€
& = 500 GeV, Process e'e-
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Distance at the face (cm) Figure 5. Distribution of distances between particle (charged and neutral) impact points at the imaging calorimeter surface depends on the physical process - width of the jet cone.
Requirements for tracker and reconstruction:
*
The tracker should reconstruct the point where the particle impacts the imaging calorimeter volume with an accuracy better then electromagnetic calorimeter cell size in order to get the best matching with reconstructed shower image. The tracker should treat low energy curling tracks carefully. The tracker reconstruction procedure should include backward propagation of all tracks to the IP including particle decays and gamma conversion vertex treatment t o get the correct particle four-momentum and composition at the interaction point.
+
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Requirements for absorber material and sampling structure: Electromagnetic part:
The distribution of distances between impact points at the imaging calorimeter face is shown in Figure 5. The distances are of order centimeters for the
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boosted jets. + The ECAL sampling structure should have the smallest Moliere radius one can reach to make compact separated electromagnetic showers in the electromagnetic part of the imaging calorimeter. + Large longitudinal segmentation is needed to allow the application of the Combined Energy-Flow method to build high quality three-dimensional shower hypotheses for different types of particles.
Hadronic part: These showers are considerably broader than electromagnetic ones, and they have big fluctuation in shape and in the energy deposited in the imaging calorimeter volume, including fundamentally undetectable energy losses due to the nuclear binding energy. The typical size of a hadronic shower is 2-3 hint.which is of order tens of centimeters. It is impossible to prevent the hadron showers from overlapping in the HCAL volume for boosted jets. The distance between particles in such jets (see Figure 5) is much less than the calorimeter interaction length for any absorber material. The requirements will come later.
Requirements on the electronic cell sizes The shower develops in the imaging calorimeter volume as a 3-d space object, so we will not separate it into transverse or longitudinal projections. The readout cell does not necessarily corresponds to an individual physical cell of the detector. One electronic cell can collect information from one or several physical volumes. Any answer for the question of cell size optimization requires a huge amount of computer simulation and reconstruction investigation for each particular variant or imaging detector option. The cell sizes are dictated by physical processes in the calorimeter volume. They will be quite different for the electromagnetic and hadronic parts of the imaging detector due t o different physics in both of them. The building of the particle type hypothesis for each cluster is important for the definition of cell size. The electromagnetic showers in the calorimeter volume are significantly different in shape. Nevertheless it allows one to apply a fit to the shapes and to get a good estimation of the probability to distinguish these showers between muon and hadron hypotheses.
Electromagnetic part: Two shower topologies make appearance most often in the electromagnetic
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part of the calorimeter. They influence to the definition of cell sizes. 1. Two close or overlapped gamma-showers from T O decay. Such gammashowers are quasi-parallel due to the large distance from IP, so the separation has to be done along all shower length. Two electromagnetic showers that do not overlap more than half of their width (a1 x 0 ) can be reconstructed separately if the transverse shower shape can be divided into more than four subdivisions. To fit the electromagnetic shower in 3-d space one needs more then 10 points in the longitudinal direction and 4-6 points in transverse at every layer. + ECAL granularity should be close to the 1 X O value for the particular sampling structure density. 2. Overlapping hadron or muon tracks with a gamma-shower. The track should be resolved in the shower background. The direction of the track can be quit different from the shower direction due to the bending in the big magnetic field. + This increases the significance of the longitudinal segmentation in comparison with that in the first case. Hadronic part:
The hadron shower spatial variations are much larger than the electromagnetic ones because more processes are involved in their development. Such a behaviour does not allow the application of any kind of hypothesis to that shower (at the level of different hadron type). For example, to distinguish a neutral hadron from a charged one. The charged hadrons easily run 1-2-3 A0 though the calorimeter before the first nuclear interaction - that is a rather big distance. The track bends at such a distance in a big magnetic field and the cluster that is created after the first hadron interaction can be found along this helix prediction with reasonable accuracy.b The hadron transverse shower shape density has three components (see Figure 6 ) . 0 The first is the primary ionization track. 0 The second is the narrow core that is mostly made of the electromagnetic part of the hadron cascade. 0 The third is the pure hadron tail around the axis with an exponential behaviour and M Ai,t. slope. ‘ bThe same effect of bending shifts the cluster center if one use the “old” reconstruction method of cluster searching based on angular space clustering or cone algorithm. cWe will not discuss the neutron component of the shower because the picture was made for the Fe-Sc structure that has a negligible neutron component.
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+ The cell size for hadron part of the imaging calorimeter should be close to the size of the transverse hadron shower core for the first few interaction lengths to collect the shower core along the predicted trajectory. The cell sizes should be close to the 1XOvalue for the particular sampling structure to follow this requirement. + The HCAL sampling structure should have the smallest XOvalue t o make better shower separation in the hadronic part of imaging calorimeter. . ,
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0 10 20 30 40 50 60 70 80 Distance from shower axes (cm) Figure 6. The radial distribution of hadronic shower energy density for particles that have MIP in the electromagnetic part of the imaging calorimeter.
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P momentum (GeV) Figure 7. T he integral energy fraction that carried by the particles with momentum P (in percent/0.5GeV) for e+e- =$ tf events at 500 GeV E C M .
6. Compensation and Combined Energy-Flow Requirements on the imaging calorimeter energy resolution: The first order of significance for the Combined Energy-Flow method is the shower separation in space and reconstruction of an individual shower correctly. The energy collected along the predicted shower direction is used in the substitution procedure. So, the energy resolution plays an important role during the reconstruction, but not the first one. The usage of the tracker and ECAL for measurement of about 90% of the energy allows one t o relax the requirements on the hadron part of the imaging calorimeter energy resolution. =+ The energy resolution of the ECAL mostly depends on the mass resolution for the pure electromagnetic processes at the parton level (e+e- + Z o H o + qQ^Iy) that we do not discuss here. It should not be worse then 12-13%/@ (see TDR14).
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The dependence of the integral energy fraction carried by particles with momentum P is shown at the Figure 7. From this picture one can see that the biggest part of the energy in an event is carried by low-energy particles (80 % of energy by particles with momentum less then 30 GeV/c). It leads to less significance of the constant term and more significance of the sampling fluctuations. The hadron calorimeter energy resolution should be as good as sampling fluctuations allow in intermediate energy region. When we are talking about sampling fluctuations then we should keep in mind that both the HCAL and ECAL sampling structures should keep the smallest value of X O , as shown above.
+
Compensation:
The imaging calorimeter energy resolution is a second order parameter in the Combined Energy-Flow reconstruction technique. If this is so, calorimeter compensation and the constant term of the energy resolution come in as third order of significance in the reconstruction procedure, and in its influence on the final result - that is the jet energy and di-jet mass resolution. To prove this statement let us look at the ZEUS detector as an example: ZEUS has a very good quality, well compensated calorimeter with maybe the best hadron energy resolution, but the jet energy resolution in the ZEUS detector is bad in comparison with hadron energy resolution". In the reconstruction procedure ZEUS applied the Energy-Flow technique but, a rather small magnetic field and coarse granulated electromagnetic and hadron calorimeter do not allow this technique to achieve a good jet energy resolution.d The same situation is true for the all LEP detectors mostly due to bad calorimeter segmentation. The imaging detector (if we follow the Combined Energy-Flow requirements) will have two separated parts, electromagnetic and hadronic, with different absorbers and sampling structures, so it will be a non-compensated calorimeter by default. An intermediate atomic number absorber material (Fe) has less neutron yield of the hadronic cascade, leading to smaller overlap of showers in the case -
d The volume of hadronic part of the calorimeter, where compensation of the binding fluctuation occurred (by neutrons signal registration) significantly larger ( w one order of magnitude) than the main part of the hadron shower energy deposition, so this properly leads to the deterioration of the energy resolution f o r the overlapped hadron showers. This is might be one of the reasons why compensation did not work in the case of jet energy measurement in old detectors.
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4.
5.
6.
7.
8. 9. 10. 11. 12.
13. 14. 15. 16.
A. Bhatti et al., (CDF Collaboration), Review of Jet Clustering a t Tevatron, talk at CALOR2000 Conference, Annecy (2000). S. Aid et al., (H1 Collaboration), A Measurement and QCD Analysis of the Proton Structure Function &(2, Q 2 )a t HERA, Nucl. Phys. B470, 3 (1996). C. Adloff et al., (H1 Collaboration), Diffraction Dissociation in Photoproduction a t HERA, Z. Phys. C74, 221 (1997). C. Adloff et al., (H1 Collaboration), Measurement ofNeutral and Charged Current Cross-Section in Positron-Proton Collisions a t Large Momentum Transfer, Eur. Phys. J. C13, 609-639 (2000). C. Issever et al., (H1 Collaboration), The calibration of the HI liquid Argon calorimeter, Proceedings of the IX CALOR2000 Conference, Annecy , 603-608 (2000). G. Briskin, Diffractive Dissociation in ep DIS, Ph.D. Thesis (1998). J. Breitweg et al., (ZEUS Collaboration), Eur. J. Phys. C1, 81 (1998). S. Chekanov and S. Magill (ZEUS Collaboration), Jet Energy Corrections with the ZEUS Barrel PREshower Detector, talk at CALOR2000 Conference, Annecy (2000). M. Wing (ZEUS Collaboration), the ZEUS Detector, talk at CALOR2000 Conference, Annecy (2000). J. Damgov, L. Litov, Application of neural networks for energy resolution, NIM A 482, 776-778 (2002). S. Kunori (CMS Collaboration), Jet Energy Reconstruction with the CMS Detector, talk at CALOR2002 Conference, Pasadena, (2002). M. Wielers (ATLAS Collaboration), Performance of Jets and missing ET in ATLAS, talk at CALOR2002 Conference, Pasadena, (2002). N. Isamu (OPAL Collaboration), Jet Measurement a t OPAL, talk at CALOR2002 Conference, Pasadena, (2002). A. Kiiskien (DELPHI Collaboration), Development on Jet Reconstruction by DELPHI, talk at CALOR2002 Conference, Pasadena, (2002). D. Foumier, Overview of Calorimetry at LHC, talk at CALOR2002 Conference, Pasadena, (2002). ZEUS Collaboration, Search for Resonances Decaying to e+ - j e t in e+p Interactions a t HERA, preprint, DESY 00-023, (2000). M. Minard (ALEPH Collaboration), Jet energy Measurement with the ALEPH detector a t LEP2, talk at CALOR2002 Conference, Pasadena, (2002). S. Dell’Agnello (CDF2 Collaboration), CDF2 Integrated Calorimetry Environment, talk at CALOR2002 Conference, Pasadena, (2002). TESLA Technical Design Report, DESY March 2001, http://tesla.desy.de/new-pages/TDR-CD/start .html F. R. K. h j i i , M. Peskin, Reference Reactions for the World-Wide LC Study, (2001), http://www.slac.stanford.edu/ mpeskin/LC/refrxns.html. V. Morgunov, Energy-ffow method for multy-jet effective mass reconstruction in the highly granulated TESLA calorimeter, Snowmass2001 proceedings (2001), http://www.slac.stanford.edu/econf/COlO63O/forweb/E3l5~m0rgunov.pdf.
Calorimetry in Astrophysics Covener: T. Parnell
T. Parnell
Covener’s Report
J. Isbert
ATIC, a Balloon Borne Calorimeter for Cosmic Ray Measurements
T . Wilson
ATIC Backscatter Study Using Monte Carlo Methods in FLUKA & ROOT
V. Bonvicini
A Silicon-Tungsten Calorimeter for Cosmic-Ray Physics
R. Kossakowski
Electromagnetic Calorimeter for the AMS-02 Experiment
P. Maestro
Performances of the AMS-02 Electromagnetic Calorimeter
A. Chekhtman
The Status of GLAST CsI Calorimeter
R. Terrier
Performance of GLAST Calorimeter
0. Ganel
Cosmic Ray Energetics And Mass (CREAM): Calibrating a Cosmic Ray Calorimeter
F. Krennrich
VERITAS: A Next Generation Atmospheric Cherenkov Detector and Calorimeter for Gamma-Ray Astronomy
A. K. Tripathi
Pierre Auger Observatory: The World’s Largest Calorimeter
*K. Arisaka
EUSO and OWL: Atmospheric Cosmic Ray Calorimetry from Space
*J. Lamoureux
Calorimetry (GeV-EeV) in AMANDA and IceCube Neutrino Telescopes
*Written contribution not received
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ASTROPHYSICS
T. PARNELL U A H and Marshall Space Flight Center, N A S A E-mail:
[email protected] (Convener’s Report)
The applications of calorimetry in astrophysics cover an enormous energy range from cryogenic bolometers for 1 keV X-rays (not covered in this session) to methods that instrument large masses of Earth’s atmosphere in order t o perform measurement of cosmic particles above 10l8 eV. Energy ranges, low and often isotropic fluxes, kinds of particles to be measured and economic considerations constrain the calorimetry methods that can be employed. The papers in this session provide a sample of scientific objectives, calorimetry techniques and instrument development challenges in astrophysics. The first set of papers in this session discuss calorimetry applications for direct measurements on cosmic gamma rays, electrons and nuclei. They use more traditional particle calorimetry techniques to measure the energy along with other detectors to directly identify the primary particle. These detector systems are designed for exposure on large balloons or on spacecraft. The Advanced Thin Ionization Calorimeter (ATIC) , with a bismuth germanate calorimeter has been flown around the South Pole on a balloon t o measure the energy spectra of cosmic ray nuclei (up to Fe) over the range of 0.1 to 100 TeV. Next a silicon and tungsten calorimeter for the satellite-borne PAMELA experiment is described. It is intended to measure the spectra of electrons, positrons and light nuclei up to 0.7 TeV. Another paper describes the lead-scintillating fiber electromagnetic calorimeter to be employed in the Alpha Magnet Spectrometer (AMS). It will be flown on the International Space Station for several years t o measure the spectra of cosmic ray hadrons and electrons and search for anti-nuclei (He and heavier). A CsI calorimeter for the Gamma Ray Large Area Space Telescope (GLAST) is also described. It will extend the energy range of an electron pair telescope (which employs silicon strips and tungsten foils) t o several hundred GeV. GLAST will continue the study of high energy discrete sources such as BLAZARS (active galaxies with jets). This set of “direct” instruments concludes with the calorimeter for the Cosmic Ray Energy and
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Mass (CREAM) instrument to be flown on an “ultra-long duration” balloon flight. Along with a transition radiation detector, the tungsten-scintillating fiber calorimeter will be used to measure the spectra of cosmic ray nuclei to above 1014 eV. All these calorimeters are very thin (about two proton mfp), because the low fluxes demand a large area, but the flight vehicles limit the mass. Thus they cannot compete in energy resolution with accelerator experiment calorimeters. The second sample of calorimeters presented in this session use Earth’s atmosphere or the Antarctic polar ice cap for the calorimeter’s mass. The Whipple Observatory employs the atmospheric Cerenkov imaging technique for studying the gamma ray spectra of discrete objects such as pulsars and BLAZARS above 100 GeV. The instrument uses large mirrors with arrays of photomultipliers at the focus to track the candidate sources across the night sky. The tracking and characteristics of the imaged Cerenkov light from the atmospheric showers allow discrimination against the showers produced by nuclei. The Very Energetic Radiation Imaging Telescope Array System (VERITAS) will be more sensitive with better background rejection, and will extend down to 10 GeV, allowing comparison with future GLAST observations. The Pierre Auger Observatory (PAO) described next will provide a significant advance in cosmic ray air shower experiments which use detectors on the ground. Its large area of 3,000 square kilometers will extend the energy range above lo1’ eV and the use of 1,600 water Cerenkov counters and four “fly’s eye” atmospheric fluorescence detectors will provide important data to identify the primary particles. Not published here, but useful in describing the range of astrophysics calorimetry techniques are the AMANDA/Ice Cube and the EUSO/OWL experiments which were presented. AMANDA uses strings of photomultiplier tubes frozen deep in the Antarctic ice cap to provide a sensitive detector for high energy neutrinos which might be produced in hadronic processes in sources of cosmic rays or y-ray bursts. The Extreme Universe Space Observatory (EUSO) and the Orbiting Wide-angle Light-collector (OWL) are proposed instruments to observe about a million square kilometers of the atmosphere from space, and to measure the moving discs of nitrogen fluorescence produced by large air showers. The shower profiles would be used to identify the primary particles and to measure the cosmic ray spectra above lo2’ eV. Also, in the Cerenkov calorimetry session of this conference are two papers concerning the measurement of radio Cerenkov radiation that have potential application in astrophysics.
ATIC, A BALLOON B O R N E CALORIMETER FOR COSMIC RAY MEASUREMENTS
J . ISBERT, G. CASE, D. GRANGER, T.G. GUZIK, B. PRICE, M. STEWART, J.P. WEFEL Louisiana State University, Dept. of Physics & Astronomy Baton Rouge LA 70803-4001, USA E-mail: isbert%phunds.phys.lsu.edu
J.H. ADAMS, M. CHRISTL NASA/Marshall Space Flight Center, Huntsville, A L
H.S. AHN, 0. GANEL, K.C. KIM, S.A. NAQVI, E.S. SEO, R. SINA, J.Z. WANG, J. WU University of Maryland, College Park, MD, USA
A.R. FAZELY, R. GUNASINGHA Southern University, Baton Rouge, LA, USA
Y.J. HAN,H.J. KIM, S.K. KIM Seoul National University, Seoul, Korea
G. BASHINDZHAGYAN, E. KOUZNETSOV, M. PANASYUK, A. PANOV, G. SAMSONOV, N. SOKOLSKAYA, A. VORONIN, V. ZATSEPIN Lomonosov Moscow State University, Moscow, Russia
J. CHANG, W.K.H. SCHMIDT Max Planck-Institute fuer Aeronomie, Katlenburg-Landau, Germany
ATIC (Advanced Thin Ionization Calorimeter) is a balloon borne experiment designed to measure the Cosmic Ray composition for elements from hydrogen to nickel and their energy spectra from 50 GeV to near 100 TeV. It consists of a Simatrix detector to determine the charge of a CR particle, a scintillator hodoscope for tracking, carbon interaction targets and a fully active BGO calorimeter. ATIC had its first flight from Mcmurdo, Antarctica from 28/12/2000 to 13/01/2001, local time, recording over 360 hours of data. The constraints, the design and the operation of this balloon borne instrument are described.
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1. The ATIC design ATIC is designed primarily to measure cosmic ray spectra for elements from hydrogen t o nickel. Balloon born instruments face severe limitations in terms of size (volume, shape), weight, power and communication. 1.1. Limitations The most severe for complex instruments utilizing calorimeters are weight and communication. The maximum weight limit is determined by the size of the available balloon. For the ATIC instrument this limit was set by a 28 million cubic feet helium balloon to 32001bs. In addition to lifting the science instrument the balloon also has to carry the balloon "craft" consisting of communication electronics, a parachute and termination packages. One termination package severs the balloon from the instrument at the end of the flight, the second termination package severs the parachute from the instrument after landing. The limits for communications is set by its route and location. The fastest link at about 330kbaud is direct line-of-sight VHF, which is limited t o about 600 miles. For distances outside this area satellites are used at a rate of about 4kbaud. ATIC generates data at about the rate of the line-of-sight link. 1.2. The ATIC instrument The most efficient way to determine energy utilizing a calorimeter for a given weight is ionization calorimetry. This technique utilizes the interactions of cosmic ray nuclei in a low Z target. The resulting secondary pions decay into high energy photons which then start an EM shower in the calorimeter. This is used as the energy measurement for the incident nucleus. In order to determine the energy spectra for each cosmic ray species the following quantities need to be measured:
(1) The charge of the cosmic ray particle, (2) Its energy and (3) The abundance of each species. The ATIC balloon instrument is composed of two major subsystems: the target module and the calorimeter. The target module has 4 functions:
(1) Provide the low Z target for the cosmic ray nuclei to interact (2) Determine the charge of the cosmic ray nuclei, (3) Provide a trigger for the instrument
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(4) Provide tracking in combination with the calorimeter. The calorimeter has 2 functions: (1) Determine the energy of the cosmic ray, (2) Provide tracking in combination with the target module. 1.3. The Target Module
Figure 1 shows a cross section of the ATIC instrument. The target module consists of (from top to bottom): a silicon matrix detector array, three plastic scintillator XY planes, the first (Sl) placed directly below the silicon matrix detector, followed by lOcm of carbon target, the 2nd scintillator XY plane (S2) and 20cm of carbon target and then the 3Td scintillator XY plane (S3).
\
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Silicon Detector Si
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s1
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Figure 1. Cross section of the ATIC Instrument.
A potential problem for charge determination in the presence of calorimeters are particles back scattered from the shower into the detectors above once the energy of the cosmic ray exceeds a few TeV. Simulations of high energy protons in the ATIC experiment indicate that, indeed, as the proton energy increases the number of "back-splash" particles per unit area increases in all three
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scintillator planes as well as the silicon matrix detector, potentially adding to the charge signal and degrading the ability to distinguish between Protons and Helium. To combat this effect both charge detectors are segmented, thereby decreasing the probability of back scattered particles passing through the same detector element as the cosmic ray. The Silicon matrix is the primary charge detector, supplemented by the topmost scintillator plane. The Silicon matrix detector consists of 4480 silicon pixels, 1.5 x 2.0 cm in size (Adamsl), covering an area slightly larger than the aperture defined by the trigger scintillators. The individual pixels are read out with a specially designed low power application specific integrated circuit (ASIC), the CR1.4 consuming only 6.6 mW per channel. A chip consists of 16 channels. The analog output of this chip is digitized with a 16 bit ADC, thereby covering the charge range from protons to nickel in a single ADC range. Each of the three scintillator detectors consists of two planes composed of individual strips of plastic scintillator rotated 90" to each other. The individual strips are viewed by photomultiplier tubes at each end. Each photomultiplier is read out by two channels of a custom designed low power ASIC, consisting of 16 channels of a preamplifier, ADC and two discriminator outputs for the trigger logic. Each channel consumes only 14mW of power. The front end electronics containing these ASICs and their support electronics is mounted directly behind the photomultipliers. defining the active aperture of the instrument
1.4. The Calorimeter The calorimeter module at the bottom of the instrument consists of a "package" of 320 BGO crystals, each 2.5 cm by 2.5 cm by 25 cm in size and placed into 8 trays of 40 crystals each, covering an active area of 51 x 51 cm2. Alternating layers are rotated 90" relative to each other to form 4 X and 4 Y layers. Each BGO crystal is wrapped in teflon tape and covered with aluminum coated mylar foil for light tightness and viewed by a single photomultiplier tube, a Hamamatsu R5611-01. A light attenuator is placed on the front face of each photomultiplier to keep the readout linear over the entire signal range. The PMTs and the required electronics is mounted in a box directly to two opposing sides of each tray. For calibration and liveliness tests a light emitting diode is mounted onto the side of each PMT. To measure particle energies up to 100 TeV the readout device has to cover energy deposits from about 5 MeV to over 10 TeV in each individual crystal. To readout the high dynamic range of the signals in a single crystal of 2x106 the readout of the photomultiplier tube is split into three gain ranges. This
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is accomplished by utilizing three dynode pickoffs each read out by its own preamplifier channel. The digitization is accomplished utilizing the same ASIC used for the scintillators. The absolute energy calibration of the calorimeter is done by first calibrating the highest gain range of every BGO crystal with cosmic ray muons. Then the higher energy ranges (=lower gain) are calibrated using the overlap between ranges. The slope in the linear region determines the ratio of low E range to medium E range. The ratio of the high E range to the medium range is determined using the overlap region of these ranges. Utilizing this bootstrapping calibration mechanism, it is possible to determine the deposited energy of particle showers in the fully active BGO calorimeter very accurately. 2. The ATIC Trigger
The ATIC experiment trigger needs to fulfill two requirements:
(1) It must trigger on potential events which pass through the active aperture of ATIC, and (2) It has to set an energy threshold Requirement 1 is fulfilled by deriving a trigger from the top (Sl) and bottom (S3) scintillator of the target module. Requirement 2 is fulfilled by utilizing discriminators on the BGO crystals and form an energy dependant trigger signal. These two triggers are formed separately due to their different timing characteristics. The plastic scintillator hodoscope form a pre-trigger derived from the topmost scintillator plane (Sl) in coincidence with the scintillator plane below the carbon target (S3). This pre-trigger (PT) also locks the preamplifier outputs for potential readout. The energy dependant trigger, the master trigger (MT) is formed from the discriminator outputs of the BGO crystal readout preamplifiers. If both triggers fire for the same particle the pulse heights are digitized and read out.
3. Read out and control The data are stored on a hard disk of one of the computers mounted on the instrument as well as transmitted through the line-of-sight link. A subset of the data as well as housekeeping data such as temperatures, pressures, position, altitude and remaining disk capacity is transmitted through all links to for monitoring during the entire length of the flight. The instrument is controlled via commands from the ground through the same links.
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4. Summary
The ATIC instrument had a very successful long duration balloon flight from Mcmurdo, Antarctica. All detectors and their support systems worked well for the entire flight. ATIC is currently (June 2002) prepared for a 2nd flight from Mcmurdo, Antarctica in December 2002 / January 2003. References 1. Adams, J. H. et al., the ATIC Collaboration, Proc. 26th Int. Cosmic Ray Conf. (Salt Lake City), 5, 69 and 76, 1999. 2. Ganel, 0. et al., The ATIC Collaboration, Proc. 26th Int. Cosmic Ray Conf.(Salt Lake City), 5, 453, 1999. 3. Ganel, 0. et al., The ATIC Collaboration, Adv. I n Space Research, in press, 2001. 4. Guzik, T. G. et al., the ATIC Collaboration, SPIE International Symposium on Optical Science, Engineering, and Instrumentation, Denver, CO, 2806, 122, 1996.
5. Guzik, T. G. et al., the ATIC Collaboration, Proc. 26th Int. Cosmic Ray Conf. (Salt Lake City), 5, 6,1999. 6. Seo, E. S. et al., the ATIC Collaboration, SPIE International Symposium on Optical Science, Engineering, and Instrumentation, Denver, CO, 2806, 134, 1996. 7. Seo, E. S. et al., the ATIC Collaboration, Advances in Space Research, 19, No. 5, 711, 1997.
ATIC BACKSCATTER STUDY USING MONTE CARL0 METHODS IN FLUKA & ROOT
T. WILSON NASA, Johnson Space Center, Houston, Texas 77058, USA E-mail: twilsonOems.jsc.nasa.gov
L. PINSKY, A. EMPL, K. LEE, V. ANDERSEN University of Houston, Department of Physics, Houston, Texas 77204, USA
J. ISBERT, J. WEFEL Louisiana State University, Department of Physics and Astronomy Baton Rouge, Louisiana 70803, USA
F. CARMINATI, A. FASSO, A. FERRARI", P. SALA*, E. FUTO CERN, 1211 Geneva, Switzerland
J. RANFT Universiat Siegen, Fuchbereich Physik, 0-57068, Siegen, Germany
A Monte Carlo analysis, based upon FLUKA, of neutron backscatter albedoes is presented using the ATIC balloon experiment as a study case. Preparation of the FLUKA input geometry has been accomplished by means of a new semi-automatic procedure for converting GEANT3 simulations. Resultant particle fluences (neutrons, photons, and charged particles) produced by incident Carbon nuclei striking ATIC with energies up to 1 TeV/A are discussed. The analysis is part of a broad goal of simulating space radiation transport in materials science by means of the FLUKA code in conjunction with a ROOT-based interface.
1. Introduction The present study is the outcome of an ongoing investigation into nextgeneration Monte Carlo techniques for analyzing radiation transport in materials science. This is motivated by the need for a comprehensive understanding of mitigation measures for radiation protection in nuclear physics, particle * Permanent address: INFN and Dipartimento di Fisica dell' Universita, 20133 Milano, Italy.
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accelerator physics, and space exploration. The tools involved derive from sophisticated physics transport codes and prove to be invaluable in the design of particle detectors as well as cosmic-ray payloads in high-energy astrophysics, an application that will be the focus of our discussion here. The particular name for this investigation is FLEUR (Fluka Executing Under Root, website: http://fleur.cern.ch/-project/links.html). The Monte Carlo of choice is FLUKA’ which is used to simulate heavy-ion interactions at energies above a few GeV/A utilizing the newly interfaced DPMJET 11.5 event generator (although no heavy-ion interaction model is present at low energies even though transport and energy loss are simulated). FLUKA also simulates all other known particle interactions. The graphical interface will eventually be the object-oriented (00)software called ROOT2 developed at CERN, a combination which is an adaptation of the AliROOT off-line system architecture shown in Figure 1.
Figure 1. Illustration of the virtual Monte Carlo concept in ALICE’S AliROOT off-line system design, showing the transport engines FLUKA and GEANT with differing geometry databases.
2. Benchmarking and Testing FLUKA
FLUKA (http://www.fluka.org/) is a fully integrated particle physics Monte Carlo simulation package that is particularly suited for backscatter problems.
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It has many other applications in high-energy experimental physics and engineering, shielding, detector and telescope design, cosmic-ray studies, dosimetry, medical physics, and radiobiology. In order to test and validate the predictive power of FLUKA, recent studies include an analysis of the particle backscatter albedo of the Earth’s atmosphere as measured by AMS3 (Alpha Magnetic Spectrometer) , and the Earth’s atmospheric neutrino flux4. Additional benchmark presentations and references are available at the FLUKA website. 3. The Geometry Conversion Technique
A roadblock in Figure 1 has been the inability of the GEANTS community to convert their rich heritage of G3 detector geometries directly into a FLUKA input file, except via G4. Such a technique would save considerable time, and the present study illustrates how to do this. Conversion of a complex geometry from GEANT3 to FLUKA is not a trivial step because of the fundamentally different input method adopted by the two codes, a feature that seems to be one reason GEANT3 users avoid using FLUKA. A procedure has been designed to extract the geometry and related features from an existing GEANT3 simulation in double precision. The extracted information is then transformed into an equivalent FLUKA input by a program called flex4 (FLUKA for ex-GEANT3 users). The GEANT3 concept of detector sets is retained and can be applied to the (standard) FLUKA output or used in FLUKA user routines. Only a subset of the GEANTS shapes is implemented at this point. The detailed conversion technique will be published elsewhere5 and a tutorial will be provided at the FLEUR website. 4. Brief Description of the Instrument Geometry Studied
For a realistic assessment of the converter, we selected the ATIC6 balloon payload geometry. This experiment provides another opportunity for examining a cosmic-ray instrument design using the current version of the DPMJETinterfaced FLUKA. Although this paper is not benchmarking the code against ATIC flight data, it does highlight the possibilities and the advantages of having a physics model that fully understands the intrument’s performance. ATIC is a cosmic-ray astrophysics collaboration led by Louisiana State University, involving the University of Maryland, Marshall Space Flight Center, Southern University, and a number of international partners. ATIC is designed to look at the cosmic-ray composition from 100 GeV/A to 10 TeV/A. It consists of a telescope of silicon strip detectors on top of a set of carbon interaction targets followed by a BGO (Bismuth-Germanium-Oxygen, BidGe3012) calorimeter, with triggering scintillators interspersed at various points. The
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experiment was flown near the top of the atmosphere for an extended time in Antarctica during January 2001 and additional flights are planned.
5. Resultant Backscatter Albedoes A total of 1600 Carbon nuclei events at 1 TeV/A normally incident but slightly offset from the central Z-axis (1.24 cm in X and Y) of the ATIC instrument were simulated. 1000 similar events at 100 GeV/A were also conducted, for side-by-side comparison of the effect of a 10-fold increase in energy. A histogram of the energy deposited in the top, first layer of the ATIC silicon detector is given in Figure 2, represented by the shaded spectrum. The peak at 5.29 MeV is the energy deposited by the primary C nucleus in the central Si pixel. A mzp deposits 147 keV in Si, times Z2 with Z=6 for Carbon, and the peak follows as it should.
counts 1o4
FLUKA - ATIC simulation raw energy spectrum silicon detector, first layer
1o3 1o2
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1 0
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MeV Figure 2. A raw energy spectrum in total counts from Carbon incident at 1 ATeV along the central axis of ATIC. A similar spectrum at 100 AGeV was generated for comparison.
The unshaded spectrum corresponds to the backscatter albedo. This is the total energy spectrum of the secondary radiation produced by the impact of the primary C, being the sum or integral of all charged plus neutral particles. One would expect, for example, that thermal and evaporation neutrons are principal contributors to the unshaded spectrum below 4 MeV. The fluence plots in Figure 3 represent a decomposition of the energy spectrum in Figure 2 into its component contributions from charged and neu-
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plots as an expanding gas or cloud of particles produced by the excitation or perturbation from the impacting C nucleus. This helps visualize why the flux is moving backwards (to the right in Figure 3) with respect to the calorimeter’s center of mass at (X,Y,Z)=(O,O,-15), constituting backscatter. The intent of our study has not been to re-design the ATIC instrument but rather to benchmark changes in the FLEUR adaptation of FLUKA. In several respects, the fluence plots in Figure 3 raise interesting questions. The neutron balance plot, for example, indicates the presence of neutrons in the very top Si layer (Sl) of the instrument (Z=45 cm). As space-borne cosmic-ray detector technology exceeds 1 TeV/A one can use Monte Carlos such as FLUKA to evaluate the physics of ever-increasing neutron backscatter contamination for triggering schemes as well as the interpretation of certain data. The photon fluence in Figure 3 is equally interesting. Supposing one might want to place a transition radiation detector (TRD) above the calorimeter (Z > 0 cm), the backscatter photons can affect TRD triggering schemes. Thermal and evaporation neutrons can be attenuated by a layer of H-rich material such as plastic due to elastic scattering of neutrons by protons. Other materials can alter both the photon and neutron backscatter. In any case, the utility of FLUKA for assessing the optimal absorption layer at the top of the calorimeter (Z=O cm) for mitigating backscatter is obvious. 6. Conclusions
We have developed a semi-automatic procedure5 to facilitate the conversion of simulation problems involving GEANTS designs into FLUKA. Successfully applied to the ATIC instrument, a preliminary study of the backscatter albedo has been performed using FLUKA with its newly implemented DPMJET event generator module. A simplified conversion of numerous G3 particle detector designs using FLUKA seems feasible now as next-generation Monte Carlos continue t o evolve. References 1. A. Fass6, A. Ferrari, J. Ranft, and P. Sala, Proc. Monte Carlo 2000, 159 and 955
(Springer-Verlag, Berlin, 2001.). 2. R. Brun, et al., Proc. of Computing in High-Energy and Nuclear Physics (CHEP) (Elsevier, Berlin, 1997). 3. P. Zuccon, et al., ICRC-2001 (Copernicus Gesellschaft, Hamburg, 2001). 4. G. Battistoni, et al., ICRC-2001 (Copernicus Gesellschaft, Hamburg, 2001). 5. A. Empl, et al., Comp. Phys. Comm., to be submitted. 6. Isbert, J . , et al., these proceedings.
A SILICON-TUNGSTEN CALORIMETER FOR COSMIC-RAY PHYSICS
V. BONVICINI, M. BOEZIO, P. SCHIAVON, G. SCIAN, A. VACCHI, G. ZAMPA AND N. ZAMPA University of lkieste and INFN Sezione di lkieste, via A . Valerio 2, 1-3137 'Iheste, Italy E-mail: bonviciniOts.infn.it
E. MOCCHIUTTI Royal Institute of Technology, AlbaNova University Center (SCFAB), S-10691 Stockholm, Sweden A silicon-tungsten imaging calorimeter has been designed and built for the PAMELA satellite-borne experiment. The main physics task is the measurement of the flux of antiprotons, positrons and light nuclei in the cosmic radiation. The calorimeter is made by 22 layers of tungsten (each 0.74 XO thick) interleaved with X-Y silicon sensor planes. The signals are read out by a dedicated custom VLSI front-end chip, the CR1.4P, with a dynamic range of 7.14 pC or 1400 MIPS (Minimum Ionizing Particle) and self-trigger capability. We report on the calorimeter design details, the expected performance in PAMELA, the experimental results obtained in test beams and their comparison with simulations.
1. Introduction: the PAMELA experiment The PAMELA mission is part of the Wizard-RIM (Russian-Italian Mission) program, which foresees several space experiments with different scientific objectives. Two missions of the program (RIM-0 and RIM-1) have already been carried o ~ t ~ 1 ~ 1 ~ . The PAMELA4 experiment (RIM-2 mission) has the scientific goal of measuring the cosmic radiation over a wide energy range with unprecedented accuracy. The PAMELA apparatus will be installed on-board the Russian satellite Resurs-DK1, which will be launched in early 2003 with a Soyuz launcher. Its sun-synchronous, nearly polar orbit at 600 km of altitude will allow the measurement of the low-energy component of cosmic rays when the instrument is near the poles. The main objectives of the experiment are the precise measurement of the positron flux from 50 MeV to 270 GeV and of the antiproton flux from 80 MeV to 190 GeV, as well as the search for anti-helium with a sensitivity of in the E / H e ratio. For further details see Bonvicini et al.4.
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The structure of PAMELA is similar to the one used by the Wizard Collaboration in its stratospheric balloons experiments5. The PAMELA apparatus is composed by the following detectors: 0
0
0
0 0
A system of plastic scintillators that includes: a time-of-flight counter (TOF), providing dE/dx measurement, timing information and the trigger for data acquisition, and an anti- coincidence system (ANTI), which identifies those particles that enter the spectrometer from outside its geometrical acceptance; A Transition Radiation Detector (TRD), made by 1024 Xe/Co2- filled straw tubes; A magnetic spectrometer (SPE), formed by a permanent magnet (providing a field of 0.4 T) and a tracking system realised with 6 layers of double-sided silicon microstrip detector; A Si-W electromagnetic calorimeter (CAL, see next sections); A plastic scintillator counter (S4) placed under the calorimeter for triggering of high energy (> 100 GeV) electrons.
Furthermore, a neutron counter is foreseen to be installed in the payload along with the PAMELA apparatus, just below S4. Its purpose is to work together with the calorimeter for measuring very-high energy electrons (see section 5). PAMELA has been designed taking into account the strict mass (430 kg) and power budget (350 W) limitations imposed by the satellite, as well as the vibration and shock loads occurring during the launch phase. 2. Design characteristics of the PAMELA Imaging Calorimeter The PAMELA calorimeter is a sampling calorimeter made of silicon sensor planes interleaved with plates of tungsten absorber. The instrument was designed aiming to an excellent granularity, both in the longitudinal (Z) and in the transversal (X and Y) directions. Longitudinally, the granularity is given by the thickness of the absorber layers, which is 0.74 XO (0.26 cm). Since there are 22 tungsten layers, the total depth is 16.3 XO (i.e. about 0.6 interaction lengths). This depth is not sufficient to fully contain high-energy electromagnetic showers. However, the fine granularity, along with the energy resolution of the silicon detectors, allows an accurate topological reconstruction of the showers, thus making the calorimeter a powerful particle identifier, as confirmed by simulations and experimental results (see next sections). Each tungsten plate is sandwiched between two printed circuit boards (called “frontend boards”), which house the silicon detectors and the front-end and ADC
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electronics. The silicon detectors developed for the calorimeter are large area devices (8x8 cm2), each of them is segmented into 32 large strips with a pitch of 2.4 mm and has a thickness of 380 pm. In each front-end board the detectors are arranged in a square matrix made by 3 x 3 devices and each of the 32 strips of a detector is wire-bonded to the corresponding one of the other two detectors in the same row (or column), thus forming 24 cm-long strips. The orientation of the strips of two consecutive layers (conventionally referred to as X and Y “views”) is shifted by 90”, so to have 2-dimensional spatial informations. The whole calorimeter structure is modular. The basic unit, called a “detection plane”, is formed by a tungsten plate and its two front-end boards, fully equipped with detectors and electronics. Two such detection planes are assembled together forming a “detection module”. In a module, the two detection planes are kept together by special aluminium frames to which they are bolted at the edge of the absorber plates. Figure 1 shows a picture of a
Figure 1. Photograph of a detection module of the PAMELA Imaging Calorimeter.
detection module. The 11 modules of the calorimeter can be inserted into the mechanical main structure of the calorimeter by sliding them through guides which are precisely machined inside the structure itself. The front-end electronics is based on a VLSI analog processor specifically designed for the PAMELA calorimeter, the CR1.4P6i7. For more details about the calorimeter front-end and read-out electronics, see Boezio et al.7. 3. Simulated performance.
Similar silicon-tungsten calorimeters, differing in layout, number of layers and read-out electronics, were developed and extensively studied by our group
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through simulations, beam testss and balloon flights9JoJ1J2. Throughout this activity, we had the opportunity to continuously upgrade and tune the simulation routines by comparing the simulated data with experimental results. The agreement between simulations and experimental data is excellent8J1J2. From these simulations, a Monte Carlo program based on the CERN GEANT/FLUKA- 3.21 code13 was developed to study the performance of the PAMELA calorimeter concerning the primary scientific goals of PAMELA, in particular the energy reconstruction for electrons and the identification of positrons and antiprotons in the background of protons and electrons, respectively. The simulated energy resolution of the calorimeter as a function of the energy of the electrons has a (17/fi)% dependence and the “constant term” is about 5% from 20 GeV to about 200 GeV. At higher energies the resolution starts to worsen mainly due to longitudinal losses. It is important to notice that this simulation did not consider only perpendicular tracks but, like in the real experimental situation, tracks coming at any angle inside the geometrical acceptance of the PAMELA trigger system. Therefore, the energy resolution takes into account also effects due to variations of the effective thickness of the materials and to the presence of non-active silicon volumes at the edge of the detectors. As mentioned in the previous sections, one of the main tasks of the calorimeter is to act as a powerful particle identifier to select positrons and antiprotons. In fact, in a cosmic-ray experiment like PAMELA, protons and electrons constitute most of the positive and negative components, respectively, of the cosmic radiation. The longitudinal and transversal segmentation of the calorimeter, combined with the measurement of the particle energy loss in each silicon strip, results in high identification power for electromagnetic showers. Therefore, in the electron and positron analysis, the calorimeter is used to identify electromagnetic showers whereas in the antiproton analysis it is used to reject them. Selection criteria were developed based on the experience gained using silicontungsten calorimeters in previous balloon-borne experiments”. The efficiency and contamination of the selections were studied simulating a large number of electrons, antiprotons and protons. The resulting values for different momenta spanning the entire range of interest for PAMELA are collected in Table 1.
4. Beam test results In July 2000 a prototype version of the calorimeter was tested on a particle beam at the CERN SPS, employing muons, electrons and pions up to 100 GeV/c. The calorimeter under test was equipped with all the tungsten
105 Table 1. Simulated performances: efficiencies in antiproton and electron detection versus electron and proton contamination, respectively. -
Momentum (GeV/c) 1
P efficiency 0.9192 f 0.0009
5
0.9588 f 0.0005
( 4 : ; )
20
0.9767 f 0.0004
< 6.2 X lop5 < 1.4 x 1 0 - ~ < 1.5 x 1 0 - ~
100
0.963f 0.001
200
0.954f 0.002
econtamination (2.5f0.2)X X
lop5
e+ efficiency 0.899 f 0.001
P contamination (1.9f 0.4) x 1 0 - ~
0.9533 f 0.0009
(i.4?;:;) x 10-5
0.970 f0.001
(3+;) x 10-5
0.944 & 0.002
< 3.3 x < 1.2 x
0.955 f 0.002
10-5 10-4
plates, but only 5 layers of silicon detectors (out of a total of 44) were installed. The main purpose of the test was to evaluate the performance of the CR1.4P front-end chip in real experimental conditions, to test the front-end electronics up to the ADC and to check the general behaviour of the calorimeter for electrons and hadrons, even with a few active layers. Figure 2 shows the signal distributions on one strip produced by minimum ionising particles (muons at 100 GeV/c). The signal-to-noise ratio for MIPS is
Signal (ADC values) Figure 2. Signal distribution on one strip for minimum ionizing particles (test beam data).
better than 9:1, thus confirming the expected performance of the CR1.4P
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Figure 3 is a plot obtained by considering data from all runs of electrons Momentum 100 GeV/c
Total detected energy [MIPI
Figure 3. Total number of hit strips versus total detected energy for 100 GeV/c pions and electrons (test beam data).
and pions at a momentum of 100 GeV/c. On the vertical axis is reported the total number of hit strips whether on the horizontal axis is reported the total detected energy in units of MIP. Notwithstanding the few silicon detector views installed in the calorimeter, its power of separating electrons from hadrons by means of the different shower topologies is striking. 5 . Self-triggering operation of the calorimeter
The CR1.4P chip was designed to work not only with an external trigger signal (‘‘normal” operation mode) but it was also provided with a “self-trigger” capability, i.e. it generates a logic signal when the sum of the signals of all 16 preamplifiers exceeds a certain threshold, which can be externally regulated. The self-trigger option in the CR1.4P was developed t o enhance the calorimeter’s capability to measure very-high energy (from 300 GeV to more than 1 GeV) electrons in the cosmic radiation. At present, very few measurements have covered this energy range14. Since these events are quite rare in comparison with the “normal” event rate of PAMELA, it is important to have a N
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large geometric factor in order to increase the statistics during the expected three-year lifetime of the mission. By using the calorimeter alone and requiring that the particles enter from one of the first four planes and cross at least 10 radiation lengths, the geometric factor becomes about 600 cm2sr, i.e. a factor of 30 larger than the normal PAMELA acceptance. The behaviour of the calorimeter in self-trigger mode was carefully studied by means of simulations7. The simulated energy resolution of the calorimeter in self-trigger mode is fairly constant (z12%) up to about 800 GeV. At higher energies the resolution decreases because of increasing longitudinal leakage and saturation of the signal from the strips (about 1100 MIP, this limit being set by the ADC dynamics rather than by the CR1.4P chip). Compared to the energy resolution of the calorimeter in “normal” PAMELA acquisition mode (see Figure 3), the resolution in self-trigger mode is worse (12% instead of 5% at 200 GeV), the worsening being due to the different acceptance conditions. 6. Conclusion
PAMELA will be launched in early 2003 and will allow measurement of antiparticle spectra in the cosmic radiation over a wide energy range with unprecedented accuracy. The Flight Model of the Si-W imaging calorimeter of PAMELA is presently being completed. Simulations and beam tests with the Engineering Model have shown that the calorimeter can fulfil all scientific requirements for PAMELA. References A. Bakaldin et al., Astropart. Phys. 8,109 (1997). V. Bidoli et al., Advances i n Space Research 25,2075 (2000). V. Bidoli et al., Astrophys. J. Suppl. 132,365 (2001). V. Bonvicini et al., Nucl. Instr. and Meth. A461, 262 (2001). M. Ambriola et al., Nucl. Phys. (Proc. Suppl.) B78 32 (1999). J. H. Adams et al., Proc. 26th Int. Cosmic Ray Conf., Salt Lake City, 5 69 (1999). M. Boezio et al., “A High Granularity Imaging Calorimeter for Cosmic-Ray Physics”, t o appear on Nucl. Instr. and Meth. A (2002). 8. M. Bocciolini et al., Nucl. Instr. and Meth. A333, 560 (1993). 9. R. Golden et al., Astrophys. J . 457,L103 (1996). 10. M. Boezio et al., Astrophys. J . 487,415 (1997). 11. M. Boezio, Ph. D. Thesis, Royal Institute of Technology, Stockholm (1998) (available at http://www.particle.kth.se/group_docs/admin/theses.html#phd) . 12. M. Boezio et al., Astrophys. J. 532,653 (2000). 13. R. Brun et al., Detector Description and Simulation Tool, CERN program library. 14. T. Kobayashi et al., Proc. 26th Int. Cosmic Ray Conf., Salt Lake City, 3 61 (1999). 1. 2. 3. 4. 5. 6. 7.
ELECTROMAGNETIC CALORIMETER FOR THE AMS-02 EXPERIMENT
R. KOSSAKOWSKI, F. CADOUX, V. CHAMBERT-HERMEL, G. COIGNET, J. M. DUBOIS, D. FOUGERON, N. FOUQUE, L. GIRARD, C. GOY, R. HERMEL, B. LIEUNARD, S. ROSIER-LEES, J. P. VIALLE LAPP
- BP
110, 74941 Annecy -1e-Vieux Cedex, France
G. CHEN, H.CHEN, Z. LIU, Y. LU, Z. YU, H. ZHUANG IHEP - Chinese Academy of Science, 100039 Beijing, China
F. CERVELLI, S. DI FALCO, T. LOMTADZE, G. VENANZONI INFN - Sezione di Pisa, Via Liuornese 1291, 56010 S. Piero a Grado, Italy
E. FALCHINI, P. MAESTRO, P. S. MARROCCHESI, R. PAOLETTI, F. PILO, N. TURINI, G. VALLE Gruppo Collegato INFN - Siena Physics Dept.,55 u. Banchi di Sotto, 53100 Siena, Italy
(presented b y R . Kossakowski at CA LOR 2002, Email : kossakowskiOlapp.in2p3.fr)
The electromagnetic imaging calorimeter made of Lead and scintillating fibers will identify the high energy leptons and y rays in AMS-02 experiment on the International Space Station. Physics requirements and space qualification constraints lead t o severe optimizations of the detector design, the mechanics and the electronics for this 16,5Xo calorimeter sampled by 1296 electronic channels.
1. Introduction
The AMS-02l experiment aims at measuring the cosmic ray spectra in the range of energy from GeV to TeV for three years on the International Space Station ISS. The experimental set-up consists of a superconducting magnet, a silicon tracker and a number of additional detectors, designed to measure the energy and to identify the nature of cosmic rays. These detectors are: the transition radiation detector (TRD), the time of flight (TOF) which also provides a standard AMS trigger, the ring imaging Cerenkov counter (RICH) and the electromagnetic calorimeter (ECAL). The detailed description of the AMS-02 detector can be found elsewhere2.
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The electromagnetic calorimeter, which is being constructed by an Annecy (France), Beijing (China) and Pisa-Siena (Italy) collaboration, will be a major instrument to identify electrons, positrons and y-rays and to measure their energy in particular in the high energy part of the spectrum. The ECAL is an imaging calorimeter consisting of 9 modules made of layers of Lead and scintillating fibers (Figure 1). Each module has a 648x648 mm2 section and 18 mm depth, which corresponds to 1.8 radiation lengths. In two successive modules the fibers are rotated by 90 and follow on X or Y direction. The fibers of a module are read only at one end by the photomultiplier R7600-00-M4 from Hamamatsu3, placed alternatively on each side. One photomultiplier consists of 4 independent pixels. In this way the elementary cell of the calorimeter has the dimension of 648x9 mm2 (or 9x648 mm2)in X-Y directions and 9 mm in the Z direction. It corresponds roughly to a 0,5 Molire radius for the transverse dimension of the electromagnetic shower and to a 0,9 radiation length in the longitudinal direction. A particle impinging vertically on the ECAL crosses about 16,5 radiation lengths and the longitudinal profile of the electromagnetic shower is sampled by 18 independent measurements (Figure 1).
Figure 1. ECAL for the A M S - 0 2 experiment inside the supporting structure. 324 photomultipliers will be housed in the lateral panels. The electromagnetic shower is sampled in X and Y directions by scintillating fibers glued to the inside of the grooved lead foils.
The major challenge for the photomultiplier and for its front-end electronics is related to the very large dynamic range of light pulses created in optical fibers by cosmic rays. The signal in the photomultiplier ranges from a few photoelectrons for minimum ionizing particles (MIP) to about lo5 photoelectrons for electromagnetic showers corresponding to very high energy particles (for instance an electron of 1 TeV en erg^)^. Power consumption for all ECAL electronics (including PMT bleeders) is limited to 100 W.
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Another challenge comes for mechanics of the ECAL. The total weight is limited to 630 kg (the weight of the Lead the fibers is 512 kg), first resonance frequency of the structure must be higher than 50 Hz and it has to support vibrations and accelerations up to 27g during the space qualification tests. All elements have to be designed to support 30 000 thermal cycles during 5 years of orbiting. The ECAL will be dipped into the stray magnetic field of the superconducting magnet, ranging up to 300 Gauss. The weight budget allowed for the detector and the space available between photomultipliers are very limited, which implies a fine optimization between the response of the photomultipliers on the magnetic field and the design of the magnetic shielding. In the following sections we will present the performances of the photomultiplier and its front end electronics and the design of the magnetic shielding and light collection system incorporated into the mechanical structure.
+
2. Photomultiplier and its front end electronics The total of 324 photomultipliers R7600-00-M4 from Hamamatsu will be used. The resistance for vibrations, resistance for magnetic field, square form, compactness and low weight were the major factors leading to the choice of this space qualified photomultiplier. The properties of R7600-00-M4 were extensively studied in order to optimize its dynamic range4. As mentioned in the introduction, the expected light signal from the calorimeter ranges from a few photoelectrons to lo5 photoelectrons. Several types of bleeders were tested and the dynamic range for each bleeder were determined using the LED light pulses. The deviation from the linearity was detected by comparing the PMT response for the signal of two LEDs flashing simultaneously with the sum of responses to LEDs flashing individually. As can be seen in Figure 2, for a given bleeder and given high voltage, the saturation occurs at the same output charge for all four pixels of the PMT. Figure 3 shows the relation between the number of photoelectrons at the saturation point and the gain of the photomultiplier for two different bleeders. One can observe that the saturation point differs by a factor of 5 between these two bleeders. Choosing the saturation at the level of lo5 photoelectrons and B type bleeders(see reference5 for detail) sets the gain at lo5. It was checked that in these conditions the signal corresponding to about 9 photoelectrons (expected for MIPS) can be clearly separated from the background (Figure 4 ). As a result, the design of the front end electronics (dedicated ASIC chip) was made to accept signals from 30 fC to 2 nC6. In this front end chip signals from PMT anodes are separated to low and high amplitude parts (ratio of
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Figure 2. T h e saturation of the response of the photomultiplier as a function of the collected charge (B type HV bleeder and voltage supply of -6OOV - see text).
f
a
10'
z
Figure 3. Relation between the number of photoelectrons at saturation point and the gain of the photomultiplier for two different high voltage bleeders.
-
?!.
m
E
4
35
I
450
Noturol photoslectron fluctuotion for Npa
YII
5511
MI
~1
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750
-
8
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UXI
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High Voltage (V)
Figure 4. T h e separation of the signal and the pedestal as a function of the applied high voltage. T h e natural fluctuation of the signal corresponding t o 8.5 photoelectrons corresponds t o RMS = 2,9.
about 30), than shaped and integrated with 2 pus time constant and finally treated by track and hold logic. The signal from last dynode is also proceed
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by low gain channel. Finally the multiplexer incorporated in the chip sends these 9 signals to the ADC. The whole system (including ADC) is placed on the small electronic board directly coupled to the bleeder board. The linearity tests performed on the first version of the chip are presented in Figure 5 . The right linearity was obtained in the whole expected range and the level of noise is compatible with the detection of MIPS.
High gain output (G-33
Figure 5. The output signal of the dedicated front end ASIC chip as a function of the signal delivered by the photomultiplier. One can observe a good linearity in the whole required dynamic range and the noise at the level of 10% of the MIP signal.
3. Magnetic shielding and light collection system As it was mentioned in the introduction, the stray magnetic field from the AMS-02 superconducting magnet is of the order of 200 - 300 Gauss in the region where the calorimeter is placed. The limit of the weight and the small space available between photomultipliers makes it necessary to optimize the thickness of the material used for magnetic shielding. Finite element calculations corresponding to this optimization can be found in reference7. In these calculations it was shown that when taking into account the global configuration of magnetic materials (those for both RICH and the calorimeter), the magnetic field can increase by a factor of 2 in some particular regions, where the density of surrounding magnetic materials is important. This is due to the attraction of magnetic field lines by the structure. Taking into account this effect, the local configuration of the magnetic shielding was calculated. It was shown that the shielding of photomultipliers by lmm thick, square soft iron tubes (section of 2.4 cm by 2.4 cm and length of 7 cm) lowers the magnetic field in the tube down to 10 Gauss in the central part. The measurements performed on some particular configurations confirmed the validity of calculations. It was also checked, that the response of the photomultiplier is affected
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by less than 10% by such a field4. Finally, the light collection system between the fibers of the calorimeter and the photomultiplier was optimized: leaving the fiber of the calorimeter, the light crosses successively a RTV joint, 30mm Plexiglas conical light guide, a second RTV joint and enter the photomultiplier. The collection efficiency of this set up was measured to be about 70% . 4. Conclusions
The optimization of the processing of the light signal from the electromagnetic calorimeter of the AMS-02 experiment is described. The extensive study of the R7600-00-M4 photomultiplier from Hamamatsu was done leading t o following conclusions: (1) the high voltage bleeder of the type B from Hamamatsu allows the collection of signals in the whole required dynamic range (from 3 c to 2 C , corresponding to MIP and to electromagnetic showers of 1 TeV electron respectively) with the gain of lo5. (2) the magnetic field is required to be less than 10 Gauss to limit the signal reductionto 10% .
The dedicated front-end ASIC chip was designed and the linearity of the chip was tested in the whole required dynamic range. The noise level was measured at the level of 10% of the MIP signal. The magnetic shielding of the photomultipliers was optimized by finite element calculations. It was shown that l m m thick soft iron tubes lower the magnetic field from 200-300 Gauss down to about 10 Gauss for the whole geometry of the calorimeter. Finally, the light collection system between the calorimeter and the photomultiplier was designed (RTV joints and conical light guides made with Plexiglas).
References 1. http://ams.cern.ch/AMS and references quoted there. 2. B.Alpat - AMS on ISS - talk given on the Conference Frontiers Detectors for Frontier Physics - 8th Pisa Meeting on Advanced Detectors, May 2000. 3. Hamamatsu data sheet, March 1997. 4. R.Kossakowski et al, LAPP-EXP-2002-02 / AMS Note 2002-01-03. 5. Monte Car10 simulations with Geant 4 - AMS collaboration 6. V.Herme1 - EMC electronics status - presentation on AMS Technical Interchange Meeting, CERN, Juin 2001. 7. F.Cadoux, R.Kossakowski, J.P.Vialle - AMS Note 2001-05-01.
PERFORMANCES OF THE AMS-02 ELECTROMAGNETIC CALORIMETER
F. CERVELLI, S. DI FALCO, T. LOMTADZE, G. VENANZONI Istituto Nazionale d i Fisica Nucleare INFN, via Vecchia Livornese 1291, 56010 Pisa, Italy
E. FALCHINI, P. MAESTRO, P. S. MARROCCHESI, R. PAOLETTI, F. PILO, N. TURINI, G. VALLE University of Siena-INFN Gruppo Collegato, via Banchi d i Sotto 55, 53100 Siena, Italy
G. COIGNET, L. GIRARD, C. GOY, R. KOSSAKOWSKI, S. LEES-ROSIER] J. P. VIALLE Laboratoire d’Annecy-le- Vieux de Physique des Particules-LAPP Chemin d e Bellevue, 74941 Annecy-le- Vieux, France
G. CHEN, H. CHEN, Z. LIU, Y. LU, Z. YU, H. ZHUANG Institute of High Energy Physics-IHEP, Chinese Academy of Sciences, 19 Yuquan Road Shijing Shan District, 100039 Beijing, P.R. China
A full-scale prototype of the e m . calorimeter for the AMS-02 experiment was tested at Cern in October 2001 using 100 GeV pions and electrons beams with energy ranging from 3 t o 100 GeV. The detector, a lead-scintillating fibers sampling calorimeter about 17 radiation lengths deep, is read out by a n array of multi-anode photomultipliers. T h e calorimeter’s high granularity allows t o image the longitudinal and lateral showers development, a key issue t o provide high electron/hadron discrimination. From the test beam data, linearity and energy resolution were measured as well as the effective sampling thickness. T h e latter was extracted from the data by fitting the longitudinal e m . showers profiles at different energies.
1. Introduction
AMS 02 is a large acceptance spectrometer designed to operate on the International Space Station (ISS) for three years1. The main goals of the experiment include: (1) search for nuclear antimatter with an expected sensitivity of lo-’ for He and lop7 for
c2
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(2) search for SUSY dark matter with high statistics precision measurements of the p , e+ and y spectra3 (3) astrophysical studies with high statistics precision measurements of the light isotopes (3He, B, C, 9Be, 1°Be) spectra in CR, and observations in VHE y-rays astronomy4. The accurate measurement of the e+ and y spectra at energies greater than 5 GeV requires a high rejection power (- lo4) against the CR background, mainly consisting of protons. This requirement can be achieved by a fine grained sampling e.m. calorimeter that can image the shower development in 3D, allowing for the discrimination between hadronic and e.m. cascades and the reconstruction of the shower direction5.
2. The electromagnetic calorimeter for AMS-02 The e.m. calorimeter (ECAL) of the AMS-02 experiment is a lead-scintillating fibers device6 with an active area of 648x648 mm2 and a thickness of 166.5 mm. The detector is subdivided into 9 superlayers, each consisting of 11 grooved lead foils (1 mm thick) interleaved with layers of scintillating fibers (1 mm diameter) glued by means of an epoxy resin; the superlayers are alternatively oriented along orthogonal directions. The light signal coming out from the fibers is collected by photomultipliers (Hamamatsu R7600 00-M4) through plexiglass light guides. The light guide geometry fits the active area of each of the four cathodes of the PMTs. The region delimited by one of the four PMT cathodes is called a cell (9x9 mm2); the calorimeter is subdivided into 1296 cells, corresponding to 324 photomultipliers. Further details about the detector can be found in reference?.
3. Test beam setup
A full scale prototype of the calorimeter was tested during October 2001 in CERN at the SPS X7 beam line, using 100 GeV pions and electrons with energy ranging from 3 to 100 GeV. The calorimeter was equipped with a total of 36 PMTs, therefore the effective active area was limited to 72x72 mm2 (8 instrumented cells per layer). The high voltage supply for each P MT was set to fix the working point at a gain of about lo6. The detector was read-out feeding the cathode signals into CAMAC gated charge integrating (12 bit) ADCs. No front-end sampling electronics was used during the test. Beam particles were triggered on by means of a 3-fold coincidence of scintillators aligned along the beam line.
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4. Test beam data analysis
The ECAL cells were first equalized to take into account the differences among the 36 PMTs. Two different equalization methods were used, based respectively on the cells response t o electrons and mzp's'; the first procedure was found to be the most accurate one. After equalization specific analyses were devoted to: the X O measurement and the e.m. shower profile reconstruction the study of energy linearity and leakage corrections the study of energy resolution
4.1. Measurement of the effective sampling thickness The longitudinal profiles of e.m. showers for beam energy in the range 3-100 GeV were reconstructed and fitted (Fig. 1) using the functiong
where t is the layer index and the maximum of the shower occurs at t,,, Plotting t,,,
=f.
as function of beam energy (Fig. 2) and using the relation
t,,,
= XO . log E
+ const
(2)
to fit the data, a value of X O = (9.6 f 0.3) mm was extracted, which implies an ECAL total thickness of (17.3 f 0.5) X,.
Layer
Figure 1. Average longitudinal shower profile at 50 GeV beam energy. T h e superimposed histogram is the expected average profile from the Monte Carlo.
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1 Figure 2.
10 Shower maximum t,,,
vs. beam energy.
4.2. Energy linearity
Electrons runs at different energies were used to calibrate the energy scale of the calorimeter. After the equalization, good linearity was found up to 30 GeV beam energy (where longitudinal leakage is negligible), with deviation of the order of 15% at 70 GeV and 20% at 100 GeV (Fig. 3). A leakage correction was applied at higher energies deriving the EOparameter from the average longitudinal profile fit (Fig. 1). The leakage corrected linearity shows residual small deviations (about 3% at 70 GeV and 4.5% at 100 GeV) caused by the incomplete coverage of the lateral development of the shower (due to the limited number of instrumented cells) and to dead channels. 4.3. Energy resolution
The energy dependence of the resolution of the calorimeter is shown in figure 4 where the fractional uncertainty on the energy measurement is plotted as a function of the nominal beam energy E. From the fit of data we found the energy resolution curve:
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E
w80
60
40
20
0 0
Ebeam (GeV)
Figure 3.
20
60
40
80
104
Ebeam (Ge\
Energy linearity curve before (left) and after (right) the leakage correction.
0
20
40
60
80
100
Energy (GeV)
Figure 4. Energy resolution vs. beam energy.
5. 3D shower imaging
Taking advantage of its fine granularity and geometry with alternate planes of fibers oriented along orthogonal directions, the calorimeter can image the
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longitudinal and lateral development of e.m. and hadronic showers, providing two orthogonal views for each event. In figures 5 and 6 two typical events are displayed, respectively, for an electromagnetic and a hadronic interaction. The calorimeter is capable to image showers so resolving the different topology of e m . versus hadronic events; this is essential to achieve a high e l h discrimination. A fully quantitative study of the hadron rejection power was not
X-L
vlew RUN 186 Event 252
fiview RUN 186 Event 252
Figure 5 . Image (2 orthogonal views) of an e.m. shower generated by a 100 GeV electron.
1x4 vtew RUN 171 Event 18
iy-zview RUN 171 Event 1s
t
Figure 6.
Image (2 orthogonal views) of a hadronic shower generated by a 100 GeV proton.
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possible due to the small statistics collected with hadron beams and to the limited lateral detector coverage. Rejection power will be measured in a future planned test beam. 6. Conclusions
A prototype of the e.m. calorimeter for AMS-02 was successfully tested at CERN and the measurement of its properties showed a good agreement with its expected performances. The imaging capability of the calorimeter allowed a 3D visualization of the shower development, an essential tool to discriminate e.m. showers from showers originating by the hadronic interactions of protons and pions.
References B. Alpat, Nucl. Instr. and Meth. A461,272-274 (2001). A. Dolgov, Phys. Rep. 222, 311 (1992). G . Jungman et al., Phys. Rep. 267,195-373 (1996). R. Battiston, Nucl. Instr. and Meth. A409,458-463 (1998). 5. E. Choumilov et al., Nucl. Instr. and Meth. A426,625-632 (1999). 6. M. Antonelli et al. Nucl. Phys. B 54, 14-19 (1997). 7. F. Cervelli et al. “The AMS Electromagnetic calorimeter”, CALOR2002 proc. 8. F. Cervelli et al. “Analysis of Ecal 2001 test beam data”, AMS-02 Note. 9. E. Longo and I. Sestili Nucl. Instr. and Meth. A128,283 (1975). 1. 2. 3. 4.
THE STATUS OF GLAST CSI CALORIMETER
A.CHEKHTMAN, REPRESENTING GLAST COLLABORATION Space Science Division, Naval Research Laboratory, 4555 Overlook Avenue Washington DC 20375, USA E-mail:
[email protected] GLAST is a gamma-ray observatory for celestial sources in the energy range from 20 MeV to 300 GeV. This is NASA project with launch anticipated in 2006. The principal instrument of the GLAST mission is the Large Area Telescope (LAT), consisting of an Anti Coincidence Detector (ACD), a silicon-strip detector Tracker (TKR) and a hodoscopic CsI Calorimeter (CAL). It consists of 16 identical modules arranged in a 4 x 4 array. Each module has horizontal dimensions 38 x 38cm2 and active thickness 8.5 radiation length. It contains 96 CsI (Tl) crystals arranged in 8 layers with 12 crystals per layer. The scintillation light is measured by PIN photodiodes mounted on both ends of each crystal. The sum of signals at the two ends of the crystal provides the energy measurement. The difference in these signals provides the position measurement along the crystal. The calorimeter was designed to meet the goals of good energy resolution (better than 10% for photon energies 100 MeV - 100 GeV), position resolution of l m m for photon energies > l G e V , and a rejection factor of > 100 for charged cosmic rays, under limitations on calorimeter weight (95 kg per module) and power consumption (6 W per module). The Monte Carlo simulation and prototype beam test results confirm that proposed design meets the requirements. Calorimeter production is planned t o start in 2003. N
1. Introduction
GLAST is a next generation high-energy gamma-ray observatory designed for making observations of celestial gamma-ray sources in the energy band extending from 20 MeV to more than 300 GeV. The principal instrument of the GLAST mission is the Large Area Telescope (LAT) that is being developed jointly by NASA and the US Dept. of Energy (DOE) and is supported by an international collaboration of 26 institutions lead by Stanford University. The GLAST LAT' is a high-energy pair conversion telescope. It consists of an Anti Coincidence Detector (ACD), a silicon-strip detector Tracker (TKR), a hodoscopic CsI Calorimeter (CAL), and a Trigger and Data Flow system (T&DF). The design is modular with a 4 x 4 array of identical tracker and calorimeter modules. The modules are 38 x 38cm2. Figure 1 shows the LAT instrument concept.
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Figure 1. View of the LAT Science Instrument with one Tracker tower module and one Calorimeter module pulled away from the Grid. GLAST is a 4 x 4 array of identical Tracker and Calorimeter modules.
2. LAT technical description The principal purpose of the LAT is to measure the incidence direction, energy and time of cosmic gamma rays while rejecting background from charged cosmic rays and atmospheric albedo gamma rays and particles. The data, filtered by onboard software triggers, are streamed to the spacecraft for data storage and subsequent transmittal to ground-based analysis centers. The Tracker provides the principal trigger for the LAT, converts the gamma rays into electron-positron pairs, and measures the direction of the incident gamma ray from the charged-particle tracks. The primary tasks of the GLAST calorimeter2 are to provide an accurate measure of the energy of the shower resulting from pair conversion of incident gamma rays in the tracker, and to assist with cosmic-ray background rejection through correlation of tracks in the silicon tracker with the position of energy deposition in the calorimeter. The calorimeter also provides triggers to the LAT, particularly for very large energy depositions. 3. Calorimeter design overview
The calorimeter is comprised of a segmented thallium-doped cesium iodide, CsI(Tl), scintillation crystal array.
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To achieve the required energy coverage and resolution, the calorimeter is 8.5 radiation lengths (8.5Xo)deep. An additional depth of 1.5Xo resides in the tracker. To assist in track correlation for background rejection and to improve the energy measurement by shower profile fitting, the calorimeter is segmented into discrete detector elements and ,arranged into a hodoscopic or imaging configuration and read out using PIN photodiodes. The design of a single calorimeter module is shown on Figure 2.
CsI Detectors 3seout
Carb
Elect
Mounting Baseplate
A1 EM1 Shield
Figure 2. Exploded view of a single Calorimeter module. Eight layers of 12 CsI Crystals are readout by P I N photodiodes and electonics on the four module sides
Each CAL module contains 96 crystals of size 26.7 x 19.9 x 326mm3. The crystals are individually wrapped for improved light collection and optical isolation, and are arranged horizontally in 8 layers of 12 crystals each. Each layer is aligned 90 degrees with respect to its neighbors, forming an x-y array. The spectral response of the PIN photodiodes is well matched with the scintillation spectrum of CsI(Tl), which provides for a large primary si5nal ( N 5000 electrons collected in 1.5cm2 diode per MeV deposited), with correspondingly small statistical fluctuations and thereby good intrinsic spectral resolution. The PIN photodiodes are mounted on both ends of a crystal and measure the scintillation light at each end of a crystal from an energy deposition in the crystal. This provides a redundancy in the energy measurement. However,
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the difference in light levels seen at the two ends of the crystal also provides a determination of the position of the energy deposition along the CsI crystal. The position resolution of this imaging method ranges from a few millimeters for low energy depositions (- 10MeV) to a fraction of a millimeter for large energy depositions (> 1GeV). The size of the CsI crystals has been chosen as a compromise between electronic channel count and desired segmentation within the calorimeter. The indicated size is comparable to the CsI radiation length (1.86 cm) and Moliere radius (3.8 cm) for electromagnetic showers. The hodoscopic array of CsI crystals is installed in a carbon composite cell structure. Aluminum side panels hold the CsI crystals in the cells, provide mounting space for the readout electronics printed circuit cards, and provide EM1 shielding. A baseplate provides for mounting of the calorimeter module to the LAT GRID structure and is integral to the strength of the GRID. As shown in Figure 2, the readout electronics for the calorimeter are mounted on the four sides of the module where they attach t o the PIN photodiodes. The major design challenges for the calorimeter electronics were 0 0
dynamic range of 5 x lo5 reduced power consumption per CsI crystal
The large dynamic range is supported by using two independent signal chains. A custom dual PIN photodiode assembly is used at each end of the crystals. The active areas of the two diodes have a ratio of 6 to 1. The larger area diode covers the low energy band (2 MeV - 1.6 GeV), while the smaller diode covers the higher energy band (- 15MeV to 100GeV). The significant overlap between the two ranges permits cross-calibration of the electronics. Each diode has dedicated preamp and shaping amplifiers that are part of a custom application specific integrated circuit (ASIC). The power for the readout electronics has been reduced by the development of analog and digital CMOS ASICs that are optimized to the performance requirements of the calorimeter. The mechanical structure is designed to have the structural stiffness to withstand environmental loads without requiring any contribution from the crystals. The honeycomb geometry of the structure, combined with light, high strength material ensures the required mechanical properties, while minimizing the amount of passive material between the CsI logs. The thickness of the wall within a layer is less than 0.4 mm and from layer to layer less than 0.8 mm. The outer walls are thicker since metallic inserts are embedded in the composite material to provides attachment point for the aluminum parts. A wrapped CsI crystal with bonded photodiodes is called Crystal Detector Element (CDE). The wrapping material - non-metalic reflector film VM2000
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from 3M - was chosen to maximize the light yield. The wide qualification temperature range (from -3OC to +50C) and the significant mismatch of thermal expansion coefficients of CsI and photodiode carrier require a chareful choice of adhesive t o bond photodiodes to crystals. After a substantial test program, we have selected a Dow Corning silicone elastomer (DC93-500) and primer (DC92-023). These materials have excellent optical and mechanical properties and provide bonds that readily survive the mechanical stresses. The CDEs are mounted independently inside the composite cells and access is granted t o each of them until the close out plates are assembled. A clearance of 0.3 to 0.5 mm allow their integration inside the cells. A silicone elastomeric cord is placed between each the corners of the cells and the chamfers of the crystals to provide a support distributed along the full length of the logs and center the CDE in the cell. The cords are stretched to reduced their diameter and allow the insertion of the log. Tkansverse vibrations of the CDE are damped by the elastomeric cords. Longitudinal motion is damped by elastomeric pads in the cell closeout. Table 1 shows the sharing of the responsibilities of collaboration countries in calorimeter manufacturing. Table 1. The manufacturing responsibilities of collaborating countries. Sweden
- Acceptance and verification of crystals from vendor -
France
Acceptance, verification
- Assemble Crystal Detector Elements (CDEs) - Manufacture mechanical structure
USA
- Manufacture front-end electronics - Integrate CDEs with structure a.nd electronics - Test and calibration
4. Calorimeter status The CsI crystal production contract with Amcrys (Kharkov, Ukraine) is in place for more than 2000 prototype and flight crystals. 240 crystals have been received in Sweden. Minor adjustments have been made in crystal length, chamfer size, and tolerance since the original specification. 650 custom prototype Dual Photodiodes (DPDs) have been received from the vendor, Hamamatsu. The photodiodes have excellent optical and electronic characteristics. Radiation testing in France indicates no problem with
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the GLAST environment. Thermal cycling tests show small cracks within the optical epoxy, with no degradation of optical or electrical performance. We expect that this problem will be readily solved by the vendor before procurement of flight DPDs. The bonding material and processes have been tested over 90 sample bonds of PIN diodes to CsI crystals. Bond strength is measured t o be the same (250N) before and after thermal cycling, significantly exceeding the tensile and shear strength requirements. Light yield tests on sample CDEs manufactured by the proposed bonding process indicate an expected yield of 7500 e/MeV for the final dimensions, which exceeds the requirement by 25The first two copies of bonding tools have been fabricated, and the first CDEs have been bonded. The prototype mechanical structure has successfully undergone vibration and thermal cycling. The calorimeter analog front-end ASIC design have evolved through 6 fabrication iterations. Essentially all required performance parameters have been demonstrated. Minor remaining issues will be tested in parts delivered in August. The first version of digital readout controller ASIC was received in March 2002 and demonstrated full functionality. Minor improvements and adjustments have been incorporated in parts to be received in August 2002. Two prototype versions of front end printed circuit board have been fabricated for testing of calorimeter readout components. The final version of PCB is currently in layout design. An Engineering Model calorimeter module is planned t o be assembled and tested in late 2002 and early 2003. The modified production schedule includes following milestones: CsI crystal production: Oct 2002 - Oct 2003 Calorimeter modules integration and tests: May 2002 - June 2004 Instrument integration and test: June 2004 - Sep 2005 Spacecraft integration and test: Sep 2005 - Sep 2006 Launch: Nov 2006 References 1. P. E. Michelson, "GLAST: A detector for high-energy gamma rays" Proc.
SPIE Conf. Gamma-Rays and Cosmic-Ray Detectors, Techniques and Missions 2806,B.D.Ramsey and T.A.Parnel1, Eds., Denver,CO, pp.31-40 (Aug,1996). 2. W.N.Johnson, J.E.Grove, B.F.Phlips,J.Ampe, SSingh, E.Ponslet, "The construction and performance of the CsI hodoscopic calorimeter for the GLAST beam test engineering module", IEEE IPrans. on NUC.Sci. 48, 1182 (2001).
PERFORMANCE OF GLAST CALORIMETER
R. TERRIER, M. JOHN, A. DJANNATI-ATAI Collbge de France, Paris, France E-mail: terraerOcdf.in2ppJ.fr
A. CHEKHTMAN, J.E. GROVE, W.N. JOHNSON Naval Research Laboratory, Washington DC, USA
The GLAST Large Area Telescope to be launched in 2006 is dedicated to gammaray astronomy from 20 MeV to 300 GeV. Its calorimeter consists of 16 modules of 8 layers of 12 CsI(T1) crystals arranged in an hodoscopic array. Each module is placed under a silicon tracker using tungsten converters. The calorimeter is only 8.5Xo thick . Therefore, depending on the energy regime, the shower containment is rather poor and corrections need to be applied. We present here the correction algorithms as well its the performances of GLAST calorimeter in terms of energy, position and direction, based on detailed simulations of the instrument and beam tests results.
1. Introduction
The GLAST calorimeter consists in 16 modules of 8 layers of 12 CsI(T1) crystals in an hodoscoping arrangement, this is to say alternatively oriented in X and Y directions, t o provide shower imaging capability. It is designed to measure energies from 30 MeV t o 300 GeV, and even up to 1 TeV. The energy measurement performance on such a broad energy range is limited due t o the presence of a 1.3 X o thick tracker, and due to a thickness of only 8.5 X O which limits the shower containement for high energy events. In these regimes, a correction must be applied in order to restore good linearity and energy resolution. The calibration and its impact on energy measurement is presented first. Then we will give details about the corrections applied in the low and high energy regime, and derive the energy measurement performance of the instrument. We will then briefly review the principles and performance of position estimation in the hodoscopic calorimeter. The results exposed here are based on Monte Carlo simulations of the GLAST instrument based on the GISMO toolkit'.
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2. Calibration
Since the various characterisics of the calorimeter are expected to change strongly after the launch and during the lifetime of the instrument, an inflight calibration is necessary. The galactic cosmic-rays nuclei(GCR) energy deposits will be used to calibrate the gains and response asymetry of crystals. On axis, protons deposit 11 MeV, carbon ions 390 MeV and iron around 7.4 GeV; this provides several absolute gains determination along the dynamic range5. There are several steps in the calibration process:
0
extract multi MIP events and select likely GCR fit the tracks identify charges identify mass and charge changing interactions and reject them fit dE/dx
In order to check the possibility to separate the various species of nuclei, a prototype of one module of the calorimeter5 has been tested at GSI Darmstadt beam facility. To produce a beam of secondaries, a 700 MeV/A Ni beam with a polystyrene target upstream was used. By comparing the energy deposits in the first two layers, we can easily distinguish the various nuclei produced from nickel in spite of the spread of the ion energies. It is important to note that because of the calibration, the calorimeter measures only a deposited energy. To recover an incident energy (especially in the high energy regime), we have to apply different gains offline.
3. Energy Measurement 3.1. Low energy regime
The tracker consist of silicon strips and tungsten converter layers. The upper part is made of 12 3% radiation length thick converters, and the lower part of 4 18% radiation length thick ones. At low energies (under a few hundred of MeV), the tungsten scatter the particles and absorb a large fraction of the incident energy. The tracker must be used as a sampling calorimeter. Once the vertex and direction of the gamma have been fitted, we compute all the hits in a cone of 5 times the multiple scaterring angle aperture around the incident direction and correct the energy with an angle-dependent sampling fraction. Taking the number of hits and the sampling fraction in the thin tracker part (nl, a ) and in the thick layers (122, p), the corrected energy for an incidence
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angle 8 is:
t Figure 1. Energy resolution in the low energy regime for normal incident photons. Since the energy dispersion function has large tails we give here the gaussian resolution (lower curve) and 68% resolution
The corrected energy response is linear and its resolution is ranging from 17% at 50 MeV to 7% at 500 MeV for normal incident photons. The resolution worsens with inceasing angle and in any case low-energy tails remain. This is summarized on figure 1 3.2. High energy regime
Around the GeV, a significant amount of energy starts to escape through the back of the calorimeter. Using the longitudinal segmentation, we can compute gains to be applied to the measured energy in each crystal in order to obtain the incident instead of the deposited energy. We have shown that these gains are all approximately equal to 1, except for the last layer. This is not surprising since the last layer carries the most important information concerning the leaking energy: the total number of particles escaping through the back should be nearly proportional to the energy deposited in the last layer. Using simulations we fit the energy and angle dependency of the correlation coefficient and obtain the following estimator for the incident energy. Here Ecal and Elast are the energies deposited in the whole calorimeter and in the last layer: Ecorr
= Ecal
+ a(Eca1,0 ) E l a s t
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This gives good linearity and energy resolution up to a few tens of GeV (depending on the incidence) where the shower maximum begins t o leak out of the calorimeter. To give a correct estimation, even in the highest energy ranges, we fit a mean shower profile to the partially observed profile, using the usual gamma distribution parametrization4. The shower energy and starting point are taken as free parameters, whereas the two parameters T and X (respectively shower maximum position and shower length) are taken at their mean value for the estimated incident energy. This restores a good linearity over the whole energy range and provides a good energy measurement even when the shower maximum is not contained. The energy resolution obtained at 300 GeV is 15% and 19% at 1 TeV for normal incidence photons7. [Energy resolution]
t
0.12 0.14
0.041 0.021
3
4 5678910
30 40 Energy CeV
20
Figure 2. Energy resolution in the high energy regime for normal incident photons. Since the energy dispersion function have large tails we give here the gaussian resolution (lower curve) and 68% resolution. Beyond 30 GeV the shower maximum begins to leak out of the calorimeter
Both methods have been tested during the SLAC 1999-2000 beam test. The resolutions obtained for 20 GeV electrons were 4% and 5% for the shower profile fitting. For more details, see Do Couto e Silva et al.3 4. Position measurement
The hodoscopic arrangement provides a position measurement in both x and y direction for each crystal in order to provide useful information on the shower shape to help rejecting the hadronic background, but also t o improve the di-
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rection estimation of high energy-events converted in the last tracker layers. We will detail here the longitudinal and transverse position reconstruction and performance. 4.1. Longitudinal position reconstruction
Using the asymmetry of light collection5, one can determine the position of the barycenter of the energy deposited in a crystal by:
L-R x=AL+R where L and R are respectively the left and right response of a crystal, and A the asymetry slope which is mostly dependent on surface treatment and wrapping of the crystals. Inside a layer the crystal with the highest energy deposition yields the best position estimate. The precision is limited by the intrinsic shower fluctuations, the electronic noise, and the uncertainty on A due to non-linearities, calibration etc. The feasability of the method has been demonstrated during the 1997 test beam2 where the position error in a crystal was found to be as low as 0.5 mm for a 5 GeV energy deposit. However the barycenter position is different from the incident direction intersection with the crystal because of the lateral extension of the shower. The radial and longitudinal profiles are mixed up when the incidence angle is large. Therefore we have a systematic bias at non-zero incidence angles. It depends on incidence angle, depth in the calorimeter and energy of the shower. 4.2. Transverse position
Because of the segmentation of the layer, the position given by the energy weighted mean is systematically shifted towards the center of a crystal, leading to the classical S-shape bias of the barycenter6. One can correct for this effect using the usual poatan(p1x) - p 2 z function. Once deconvolved in each layer, the position dispersion obtained is around a factor of 2 worse than in the longitudinal case. We can see on figure 3, the position dispersion obtained for 70 GeV normal incident photons for longitudinal (lower curve) and transverse(upper curve) positions. The precision is better by a factor of two using longitudinal position. The longitudinal error here is mostly limited by electronic noise, it should be noted though that an uncertainty of the asymmetry slope coming from calibration would reduce significantly this precision. The global barycenter dispersion varies from 1.5 mm at 10 GeV to 0.7mm
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at 100 GeV for normal incidence photons, once again neglecting systematic errors. ~orltfonerror 70 GeVi
Figure 3. Position error for 70 GeV photons in each layer. Upper is deconvolved transverse position, lower is longitudinal position
5 . Conclusion
GLAST calorimeter, though its relative thinness, is able to provide a satisfactory energy measurement. The expected energy resolutions for normally incident photons range from 15% at 100 MeV to 7% at 10 GeV, and 15% at 300 GeV. Besides, the hodoscopic arrangement gives acces to a good position determination allowing an efficient background rejection and an improved direction estimation for high energy events. References 1. W. B. Atwood and T. H. Burnett, SLAC-REPRINT-1992-037 Prepared for 10th International Conference on Computing in High-energy Physics (CHEP 92), Annecy, France, 21-25 Sept 1992. 2. W. B. Atwood et al., Nucl. Instrum. Meth. A 446, 444 (2000) 3. E. do Couto e Silva et al., Nucl. Instrum. Meth. A 474, 19 (2001). 4. Grindhammer,G., Peters, S., 1993, Int. Conf. on Monte Car10 Simulation in High Energy and Nuclear Physics, Tallahassee, Florida 5. Johnson, W. N., Grove, J. E., Phlips, B. F., Ampe, J., Singh, S., & Ponslet, E. 2000, AAS/High Energy Astrophysics Division, 32, 6. R. Y. Zhu, G. Gratta and H. Newman, Nucl. Phys. Proc. Suppl. 44, 88 (1995). 7. Terrier, R. et al. 2001, Gamma 2001, Baltimore, Maryland
COSMIC RAY ENERGETICS AND MASS (CREAM): CALIBRATING A COSMIC RAY CALORIMETER
0. GANEL, E. S. SEO, H. S. AHN, R. ALFORD, K. C. KIM, M. H. LEE, L. LIU, L. LUTZ, A. MALININE, E. SCHINDHELM, J. Z. WANG AND J. W U Institute for Physical Science and Technology, University of Maryland College Park, MD 20742, USA E-mail: opherOcosmicmy.umd.edu
J. J. BEATTY, S. COUTU, S. A. MINNICK AND S. NUTTER Department of Physics, Penn State University University Park, PA 16802, USA
M. A. DUVERNOIS School of Physics and Astronomy, University of Minnesota Minneapolis, MN 55455, USA
M. J. CHOI, H. J. KIM, S. K. KIM AND I. H. PARK Department of Physics, Seoul National University Seoul, 151-742, Korea
S. SWORDY Enrico Fermi Institute and Department of Physics, University of Chicago Chicago, IL 60637, USA
CREAM is slated to fly as the first NASA Ultra Long Duration Balloon (ULDB) payload in late 2003. On this 60-plus-day flight CREAM is expected to collect more direct high-energy cosmic ray events than the current world total. With three such flights CREAM is expected to have a proton energy reach above 5x1Ol4 eV, probing near 100 TeV for the predicted kink in the cosmic-ray proton spectrum. With a Transition Radiation Detector (TRD) above a sampling tungsten/scintillator calorimeter, an in-flight cross-calibration of the absolute energy scale becomes possible with heavy ions. We report on results from a 2001 beam test of the calorimeter in an SPS beam at the European High Energy Physics lab (CERN) and on the planned in-flight calibration.
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1. Introduction CREAM Science and measurement objectives
For over half a century it has been known that charged particles from outer space constantly hit the Earth’s atmosphere. The currently accepted Supernova Remnant shock acceleration model predicts the spectra of these cosmic-ray nuclei cuts off at different energies with Ecutoff 0: 2 x 1014 eV’ . This should lead to sudden changes in elemental spectra, causing a gradual change in the elemental composition of cosmic rays between l O I 4 eV and 1015 eV. CREAM (Figure 1) is an experiment comprised of a calorimeter, a TRD and a charge detector, intended to identify incident cosmic-ray nuclei and measure their energy2. From these measurements we will extract the spectra of nuclei from Hydrogen to Iron from 10l2 eV to 1015 eV, and search for a kink in the proton spectrum near 1014 eV. With the TRD and charge detector CREAM will measure ratios of primary to secondary cosmic rays, testing theoretical models of cosmic-ray passage through the interstellar medium. To enable these science objectives, the CREAM Timing-based Charge Detector (TCD) must measure particle charge with a resolution of 0.2e, the TRD must achieve an energy resolution of 15% for various nuclei (Carbon to Iron) at energies of 10s to 100s of TeV, covering a range of lo3 < y < lo5, and the calorimeter must achieve an energy resolution of < 50% with no high-end non-Gaussian tails3.
Figure 1. Schematic drawings of CREAM with and without its support structure.
2. The CREAM Detector
The TCD4 is comprised of 8 scintillator paddles in 2 layers, covering an area of 120x120 cm2. Each paddle is read out through two adiabatic light-guides by fast photo-multiplier tubes (PMT). Each PMT is read out by an array of fast TDCs that digitize the time of several threshold levels being exceeded by the leading edge of the scintillation pulse. These times are used to reconstruct the slew-rate of the pulse, proportional to the square of the particle charge.
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The PMTs are also read out via ADCs that digitize the peak of the pulse, for more accurate charge measurements of heavier nuclei. The TCD measurement is completed within 3 ns, avoiding noise from back-scattered secondaries. Transition radiation can be used to measure the Lorentz factor of relativistic heavy nuclei5, and with particle ID, their energy. The CREAM TRD is made up of two 35 cm thick modules. A foam matrix in each module functions as both radiator and mechanical support for 6 layers of thin aluminized Mylar tubes. Each 2 cm diameter tube contains a sense wire and a Xenonlmethane gas mixture. The T R signal is read out via Amplex-chip based circuitry. The radiator is optimized for lo3 < y < lo5. Target layers
Hodoscoper Calorimeter
Figure 2.
Schematic side-view of CREAM calorimeter module.
The calorimeter module6 (Figure 2) is comprised of a 20 radiation length (X,) sampling tungsten/scintillating-fiber calorimeter, preceded by a 0.5 Xint graphite target to induce incident particle interaction with a minimal weight penalty. Twenty 1 XO absorber plates are each followed by a layer of 0.5 mm fibers in 1 cm ribbons. Each ribbon is aluminized on one end and glued into a light-mixer on the other. Light is transferred t o the readout via a bundle of thin clear fibers, split into low-, mid-, and high-energy ranges. Neutral density filters with different transmission for the mid- and high-energy ranges (with none for the low-energy range) increase the ratio of signals between ranges further, bringing the dynamic range to the required 1:200,000. The signal is read by multi-pixel hybrid photo-diodes (HPD) with a dynamic range of up to 1:1,000,000. Half-way through the target, a scintillating fiber hodoscope provides tracking information to augment that available from the calorimeter. Above the target, two additional hodoscopes provide both more tracking information and charge information for those particles not in the TCD geometry.
3. Calibration Calibrating a hadron calorimeter system is at best not a trivial task7. When the system is intended to measure energies up to several PeV, and must be sensitive
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to low signals (5 MeV in CREAM) and high signals (1 TeV in CREAM), the problem becomes even more challenging. When attempting to measure shower energies not only of protons, but also of projectile nuclei up to Iron, an additional level of complexity is added. Finally, for flight calorimeters the problem is exacerbated yet further by requirements of low weight, low power, limited volume, no access in-flight, and no guarantee of recovery for post-flight recalibration. To address all the above one would ideally use testbeams of separate nuclei up to the highest expected energy, over a fine grid (1 cm pitch for CREAM), and at angles up to the highest acceptance (> 70 degrees for CREAM). In addition, one would like to have a test-beam with the same composition, angular distribution and energy spectra as those of cosmic rays, with each incident particle energy, charge and particle trajectory known accurately independent of the calorimetric measurement. Such a calibration facility, unfortunately, is not available. One is thus forced to combine different aspects of the above requirements from different calibration techniques. The CREAM calibration is divided into several phases and modes. Preflight, the calorimeter is tested in high-energy electron beams to provide an accurate assessment of detector performance and allow inter-calibration of ranges for each ribbon and between different ribbons. Proton runs are taken to validate the low energy portion of the CREAM hadronic Monte Carlo simulation. Heavy ions incident on a target produce a mixture of nuclear fragments to validate simulations of showers induced by projectiles with Z> 1. Simulation is then used to extrapolate to the highest expected energies. In-flight, shower data averaged over many events are used to maintain the inter-range calibration, and the inter-calibration between ribbons. In addition, LED flasher events monitor the HPD average gain ( e g . to help account for temperature gradients between different HPDs reading out different parts of the calorimeter). Charge injection events allow monitoring of the readout electronic chains, separate from the optical portion of the readout string. Finally, an in-flight cross-calibration is planned between the TRD/TCD system and the calorimeter. The TCD is expected to measure the charge of incident particles with good resolution. With the charge known, the energy of the incident nucleus can be reconstructed from the TRD Lorentz factor measurement. Since these are all electromagnetic phenomena, they can be modeled accurately. For a sub-sample of such events, the nuclei will interact and shower in the calorimeter. The reconstructed calorimeter-measured energy can be compared to the energy obtained from the TRD/TCD for an absolute energy calibration. After collecting data for 4-6 hours we expect to have a sufficiently large sample of events to provide a cross-calibration accuracy of 10%.
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4. Beam Test Results
In September 2001, a prototype CREAM calorimeter module was placed in the H2 beam-line of the Super Proton Synchrotron (SPS) (Figure 3). The objectives of this test were to validate the design of the calorimeter, t o measure the light yield from showers, and to validate the calorimeter simulation in the energy range available at the SPS. After calibration, the resulting longitudinal profile for 250 GeV electron showers showed remarkably good agreement with the average simulated showers of such electrons (Figure 4). The showers were well contained, with shower maximum occurring as expected, at a depth of 8 XO.Lateral profiles showed the core of the shower is nearly contained in a single fiber ribbon (1 cm width) with negligible tails beyond a 3 cm width.
Figure 3.
CREAM prototype calorimeter at the H2 beam-line.
After calibrating the readout gain, the signal from the highest-signal ribbon in layer 8 was translated to photoelectrons (p.e.). Simulations were used to estimate the energy deposit in the fiber ribbon, expressed in terms of minimum ionizing particle (MIP) energy deposit. The light yield measured by the HPD was corrected for the measured efficiency of light transmission from the ribbon through the light-mixer and clear fibers, indicating a light yield of 3.9 p.e./MIP at the end of the ribbon. A Gaussian fit to measurements with a lo6 Ru source above a fiber ribbon coupled directly to a P M T provided a value of 3.2 p.e./MIP, within 25% of the beam test measurement.
5. Conclusions Beam test results confirm the CREAM calorimeter works as expected based on high energy electron shower shapes and light yield. The CREAM calorimeter
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Beam test result : 250 GeV electron 0
experiment
- simulation
Layer number Figure 4. Experimental vs. simulated longitudinal shower profiles for 250 GeV electrons.
will be subjected to more detailed beam testing pre-flight to achieve full calibration. Calibration will be maintained through 60 or more day/night cycles by use of periodic in-flight stand-alone and cross-calibrations. Stand-alone calibrations will consist of LED events, charge-injection events, and shower data. Cross-calibration will utilize heavy nuclei crossing the TCD and TRD, interacting and showering in the calorimeter to obtain two independent measurements of incident energy, allowing absolute energy calibration.
Acknowledgments This work was supported by NASA grant NAG5-5249. The CREAM collaboration thanks John Mitchell of NASA/GSFC for coordinating the beam tests, and CERN for providing excellent beams and support for the reported testing.
References 1. P. 0. Lagage and C. J. Cesarsky, Astron. and Astroph., 118,223 (1983). 2. E. S. Seo et al. (CREAM Collaboration), Adv. in S p . Res. in press (2001). 3. H.S. Ahn et al. (CREAM Collaboration), Proc. 27th Int. Cosm. Ray Conf. (Hamburg), 6,2159, (2001). 4. J. J. Beatty et al. (CREAM Collaboration), Proc. 2sth Int. Cosm. Ray Conf. (Salt Lake City), 5, 61, (1999). 5. S. Swordy et al., Phys. Rev. D42,3197, (1990). 6. 0. Ganel et al. (CREAM Collaboration), Proc. 27th Int. Cosm. Ray Conf. (Hamburg), 6,2163, (2001). 7. 0. Ganel and R. Wigmans, Nucl. Instr. and Meth. A409, 621, (1998).
VERITAS: A NEXT GENERATION ATMOSPHERIC CHERENKOV DETECTOR AND CALORIMETER FOR GAMMA-RAY ASTRONOMY
F. KRENNRICH Physics d Astronomy Department, Iowa State University, Building 12 Ames IA 50011, USA E-mail: krennrichOiastate.edu The Very Energetic Radiation Imaging Telescope Array System (VERITAS) is a wide energy range (50 GeV - 50 TeV) imaging atmospheric Cherenkov detector that will provide a high sensitivity and good energy resolution for astrophysical y-ray sources. Recent discoveries of y-ray blazars have opened the possibility of prqbing the intergalactic IR fields by analyzing the shape of TeV y-ray spectra. Also, the search for the origin of cosmic rays using secondary y-rays requires accurate energy spectral measurements. The technical concept and design of VERITAS and its capabilities for calorimetric measurements are discussed.
1. Introduction
The objective of this paper is to give a short overview of the VERITAS instrument and discuss its capabilities to make energy spectral measurements. The third EGRET catalogue (Hartman et al. 1999) with > 270 y-ray sources has established the field of y-ray astronomy as a new discipline providing a wealth of information about supernova remnants, pulsars, cosmic rays, active galaxies and y-ray bursters. The extension of y-ray observations to TeV energies by atmospheric Cherenkov telescopes has resulted in a total of more than ten TeV sources (Weekes 2001), indicating the tip of the iceberg of the high energy end points of astrophysical photon spectra. Probing the physical emission processes of astrophysical y-ray sources, e.g., inverse Compton scattering of soft photons to high energy photons by relativistic electrons, often involves the measurement of energy spectra over several orders of magnitude in energy. This requires y-ray telescopes with a large dynamic range covering sub-GeV t o multi-TeV energies. Typically, these spect r a are approximated by power laws with curvature and exponential cutoffs, providing information about the physical conditions at the y-ray source and external absorption (pair production) phenomena. Energy reconstruction with sufficient resolution, accurate calibration and well understood systematic un-
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certainties over a large energy range is key to understanding the physics of y-ray emission processes and absorption features as seen in some active galaxies (Aharonian et al. 1999; Krennrich et al. 2001). Hence, energy reconstruction and calibration play an important role for the next generation of space-based (GLAST; see Gehrels & Michelson 1999) and ground-based y-ray telescopes VERITAS (Weekes et al. 2002), HESS (Hofmann et al. 1999), MAGIC (Lorenz et al. 1999) and CANGAROO I11 (Matsubara et al. 1999). Together, GLAST and the next generation imaging atmospheric Cherenkov telescopes (IACTs) cover energies between 20 MeV to 50 TeV, providing the energy range necessary to constrain astrophysical yray emission mechanisms, making the combined spectra extremely valuable. Space-based pair conversion telescopes can be well calibrated to a few percent accuracy using laboratory beams. Calibration of IACTs requires, due to the lack of a TeV y-ray test beam, extensive modeling of air showers and the earth's atmosphere. However, the next generation of satellite instrument GLAST and IACTs have substantial overlap in energy. This will allow a cross-calibration using an astrophysical standard candle, the most prominent one is the Crab nebula. By measuring the Crab Nebula spectrum the systematic uncertainties for the combined GeV and TeV spectra can be substantially reduced. In the following the VERITAS design and its implications for energy reconstruction, dynamic range and calibration will be discussed. 2. The VERITAS concept The VERITAS proposal is to built an array of seven IACTs of 10 m aperture. The location of the array will be at the Whipple Observatory in southern Arizona. The individual telescopes will be placed on a hexagonal grid with 80 m spacing (see Fig. 1). Individual telescopes will be based on the proven design of its predecessor, the Whipple 10 m reflector, which has been the pioneering instrument for the field of ground-based y-ray astronomy (Weekes et al. 1989). It has an energy range of 200 GeV - 20 TeV and a sensitivity of 7 0 ,/for a flux level of 1 Crab. The VERITAS detector is primarily aimed at a substantially improved flux sensitivity and reduced energy threshold, but will also provide a better energy resolution and angular resolution over existing instruments. In particular, the dominant design goal has been maximum sensitivity in the energy range of 100 GeV - 10 TeV. Minimum detectable fluxes (5 sigma in 50 hours) will be 0.5% of the Crab Nebula at 200 GeV, a factor of 20 better than the Whipple observatory 10 m telescope. VERITAS provides an unprecedented angular resolution of 0.05' (0.03') at 300 GeV (1 TeV), substantially better than any existing y-ray telescope on the ground or in space.
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Figure 1. The layout of the stereoscopic system of telescopes as at would be located at Montosa Canyon near Tucson Arizona.
The individual telescopes will be substantially improved over the Whipple 10 m telescope, providing adequate optical resolution, a wide FOV and fast and low noise electronics, in order to maximize the performance of VERITAS. The major improvements of the design are shortly described in the following.
2.1. Optics The design of the optical reflector of the VERITAS telescopes provide much better resolution to resolve the intrinsic characteristics of 7-ray Cherenkov images. A pixelsize of M 0.03" - 0.1", across a 3.5' field of view (FOV) would be desirablea. For practical considerations, cost of phototubes and readout, "Shower fluctuations limit the inherent accuracy of resolving the Cherenkov images, t o M 0.03' (300 GeV) as shown by Hillas (1989).
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the upper end of 0.15" is a reasonable compromise. The optical reflectors will be a Davies-Cotton design (Davies & Cotton 1957) consisting of facet mirrors, each with a 24 m radius of curvature. The Davies-Cotton (for details see Weekes et al. 2002) design has off-axis aberrations smaller than a parabolic reflector, showing good image quality out to a few degrees from the optic axis (Lewis 1990). For example, 100% of the light from a point source is concentrated in a 0.12" diameter circle out t o 1.0" from the optical axis. The Davies-Cotton reflector design is not isochronous, however, the time spread has a full width of 3 - 4 ns, comparable to the intrinsic Cherenkov pulse width.
2.2. Camem
Fig. 2 shows the layout of the focal plane detector for VERITAS. It consists of 499 photomultipliers with 0.15" spacing, corresponding to a FOV of 3.5". The pixelation and the FOV are two competing factors given a limited number of phototubes. The choice of pixel spacing is driven by the structure of y-ray shower images. In order to trigger efficiently on low energy y-ray events (E x 100 GeV), it is necessary that the image width is approximately matched by the pixel size - a pixelation larger than the image width would accept a large noise contamination from night sky background light, reducing the signal to noise ratio. In Fig. 2 the Cherenkov light image of a 100 GeV y-ray shower is superimposed on a VERITAS camera. Images of sub-TeV showers have a RMS width and length (depending on energy) of 0.10" - 0.15" and 0.20" - 0.30", respectively. The camera pixelation (0.15") and excellent optical quality of the reflector will provide sufficient resolution to trigger efficiently and resolve useful shower structure on this scale. The Cherenkov light from air showers is dominantly emitted from shower maximum (at 8-10 km atmospheric height) and the images are off-set from the arrival direction by 0.6" - 1.2", depending on the impact distance of the shower from the telescope. A 2.5" FOV is required to capture most of the Cherenkov image. However, a larger FOV is necessary for resolving extended sources, the detection of multi-TeV y-rays (especially for E > 10 TeV), and stereoscopic operation, making 3.5" a better choice. A large FOV also improves the energy resolution by imaging the shower over the entire longitudinal development by capturing y-ray images that are fully contained within the camera.
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2.3. Electronics In order to produce a digital image of the Cherenkov light flash with minimal noise contamination, the electronics of the recording system has to preserve the short (6-10 ns) pulse until it is digitized. To minimize the noise in the electronics, the photomultiplier (PMT) signals are amplified using fast preamps. Preliminary tests with a prototype of 30 channels showed an electronic noise level of 0.2 mV r.m.s. at 500 MHz sampling frequency. This allows also an in situ calibration of the gain of the electronics system using single photoelectron (p.e., hereafter) pulses (1 p.e. x 2 mV). Preamps also enable to operate the PMTs at a lower gain allowing observations during moon light, hence in-
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creasing the duty cycle of VERITAS by a factor of two in comparison to the Whipple 10 m telescope. The electronics also has to form a trigger decision based on the characteristics of a typical ?-ray image in an array of IACTs. The atmospheric Cherenkov technique is ultimately limited by the fluctuations from the night sky background. To estimate the lowest possible energy threshold for the VERITAS array, a careful analysis of the expected trigger rates from accidentals due to the night sky is requiredb. The trigger threshold, given in p.e., determines the energy threshold of the IACT array. The trigger of VERITAS is formed in a sequence, based on the different levels in the electronic chain. The level 1 trigger is simply a constant fraction discriminator. In order t o enable efficient triggering on compact y-ray images, a pattern trigger (level 2) can be programmed to select patterns of 2 N adjacent pixel (N = 2, 3 or 4) with a coincidence time window of 14 ns. This ensures that the accidental trigger rate from random night sky fluctuations is at a minimum level. A trigger condition of 2 3 adjacent pixels reduces the rate to 100 kHz. These local level 2 triggers from each telescope are transmitted by digital optical fiber cable to the central station. The level 2 trigger are sent through individual digital delays to account for the orientation of the shower front (delay range: 0-500 ns). The array trigger is required to be flexible for various operation modes: a single telescope trigger, using three and four telescopes independently, a trigger requiring 3 out of seven telescopes. At a threshold of 5 p.e., the array trigger (3 out of 7) produces a negligible background rate from random night sky fluctuations, at 4.2 p.e. the accidental rate is M 300 Hz. The digitization of the signals can begin, once a trigger decision has been formed. The trigger decision based on an array trigger of 3 telescopes can take up to 1 . 2 ~ assuming s operation at large zenith angles. A Flash ADC system (Buckley et al. 1999) at each telescope allows the digitized output samples of each channel to be written into a circulating memory (depth > 8ps), while waiting for the trigger decision. If a trigger arrives, the writing stops and the memory contents are examined for a signal in the corresponding time bin. 2.4. Performance of VERITAS: Simulations
Monte Carlo simulations have been used to determine the optimum configuration and to characterize the performance of VERITAS (Vassiliev et al. 1999). The design optimization was performed by the means of a full Monte Carlo bFor practical consideration, the array must trigger at a rate < 1 kHz, a higher rate would introduce significant dead time for the data acquisition system.
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simulation of air showers and the telescopes. Subsequent event reconstruction is based on established methods developed for single telescope data (Fegan 1997) and extended through several new algorithms, allowing a lower reconstruction energy threshold. Realistic operating conditions, e.g., a realistic night sky background, are given in form of input parameters such as FADC integration time (8 ns), pixel coincidence gate (14 ns), the level l trigger threshold (4.2 pe) and level 3 (telescope array) trigger coincidence gate width (40 ns).
Table 1. Number of telescopes Telescope spacing Reflector aperture/area Focal length Field of View (FOV) Number of pixels Pixel Spacing/Photocathode Size Array Trigger Telescope Triggers
7 (hexagonal layout) 80 m 10 m / 78.6 m2 12 m 3.5'
499 0.148' / 0.119' 3 telescopes out of 7 2, 3 pixels (adjacent)
The VERITAS design is optimized for maximum point source sensitivity between 100 GeV - 10 TeV. The outcome of these studies has resulted in the so-called baseline design for VERITAS given in Table 1. For further details of the optimization process see Weekes et al. (2002). The ability to detect y-ray sources can be described by the flux sensitivity of the detector. We define the minimum detectable flux of y-rays requiring a 5u excess above background (or at least 10 photons) for 50 hours of observation assuming a source spectrum given by dN/dE 0; E-2.5. The y-ray flux sensitivity of the VERITAS baseline design as a function of energy is shown in Fig. 3. The flux sensitivity is limited by different effects depending on energy. The region above M 2 TeV is limited by the collection area and therefore by photon statistics. At lower energies (200 GeV - 900 GeV) the cosmic ray electrons are the major source of background. The flux sensitivity below 200 GeV is limited by night sky background and cosmic-ray protonsc. In the lower curve, a low night sky background is assumed, the less sensitive curve is for a bright region in the sky, e.g., the galactic plane. Further performance details are given in Table 2and Weekes et al. (2002).
'Note, that a cosmic-ray muon can trigger the VERITAS array, but is easily rejected by the presence of a hadronic shower halo in at least one of the cascade images or by parallax.
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Figure 3.
The sensitivity of VERITAS for a point-source in 50 hours.
3. Energy Reconstruction and Calibration The IACT technique provides a good energy resolution for the measurement of y-ray induced air showers. The atmosphere is a fully active calorimeter with Cherenkov light emitted at all stages of the shower development. For yray induced showers above 20 GeV the Cherenkov light yield is approximately proportional to its primary energy. If the shower geometry can be measured with its location of the shower axis, impact point on the ground, height of shower maximum, and the total light density at the ground, the y-ray primary energy can be estimated with good accuracy. Simulations for VERITAS indicate that an energy resolution for individual y-ray showers of 10% - 20% can be reached. The energy resolution AE/E
147 Table 2. Characteristic Energy threshold” Flux sensitivityb
Angular resolution
Effective area Crab Nebula rate
VERITAS performance E
>lo0 GeV >300 GeV >1 TeV 50 GeV 100 GeV 1TeV 50 GeV (100 GeV) 300GeV (1TeV) >lo0 GeV
Value 75 GeV 9 . 1 10-12cm-2s-1/15 ~ mCrab 8 . 0 ~ 1 O - ~ ~ c r n - ~ smCrab -~/5 1 . 310-13cm-2s-1/7 ~ mCrab 0.14‘ 0.09O 0.03’ l.0x103m2 (l.0x104m2) 4.0x104m2 (l.0x105m2) 50/minute
aEnergy at which the rate of photons per unit energy interval from the Crab Nebula is highest. ‘Minimum integral flux for detecting a 5a excess (or a minimum of 10 events) in 50 hours of observations of a source with a Crab-like spectrum.
depends somewhat on the primary energy and ranges from M 20% at 100 GeV to 10% at 10 TeV, when using an algorithm that is based on shower core location and total light density. This can likely be improved using more advanced reconstruction algorithms taking into account a measurement of the height of shower maximum. This resolution is adequate to measure energy spectra that are power laws with curvature and/or exponential cutoffs. It is also a good match to the accuracy of spectral measurements at GeV y-rays (GLAST at 100 GeV: 10%) and X-rays (few %). For the physical interpretation of spectral cutoffs and the estimate of yray fluxes an absolute energy calibration of 10% or better would be desirable. Again, space-based telescopes achieve that by laboratory calibrations with a test beam. In contrast, the absolute calibration of the energy scale for IACTs is more difficult with a number of inherent systematic uncertainties: 1. atmospheric transparency, 2. response of the telescope, 3. variations in the instrument and atmosphere. The Cherenkov light transmission through the atmosphere is typically modeled using the “U.S. Standard Atmosphere, 1976” (U.S. Standard Atmosphere 1976). Cherenkov light traversing the earth’s atmosphere is attenuated by Rayleigh scattering, Mie scattering (Aerosols), and 0 2 and 0 3 . Pressure variations, changes in the Aerosol and Ozon concentration and their effects on the light throughput of the atmosphere and subsequent impact on energy reconstruction have been studied by Lewis (1997) and Krennrich et al. (1999). The uncertainty on the absolute energy was found t o be typically at the 5% - 7% level. An overall systematic uncertainty of the atmospheric model is estimated to 10%. The response of a Cherenkov telescope can be calibrated t o 5% - 10%
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accuracy including mirror reflectivity, light concentrator efficiency, quantum efficiency of the photodetectors, cable losses etc. Variations in the relative light throughput of the atmosphere and drifts in the instrument gain can be monitored using the cosmic-ray rates and spectrum (see also Le Bohec & Holder 2002, in preparation). The cosmic-ray rate in the Whipple telescope is typially 20 Hz allowing a 5% accurate relative calibration for 30 minutes of data taking. For VERITAS this could be done on shorter time scales with better accuracy. Together, these effects could result in a 25% uncertainty (sum of errors) for the absolute energy estimate of IACTs, reason enough to develop more accurate calibration procedures. An alternative method could be to capitalize on the accurate calibration of space-based y-ray detectors. The substantially increased collection area of GLAST between 10 GeV - 1 TeV and the lower energy thershold of IACTs (VERITAS 50 GeV, MAGIC 20 GeV) might provide sufficient overlap in energy between the space-based and ground-based technique. The y-ray emission from the Crab Nebula is a strong and constant y-ray source that has its peak emission between 50 GeV - 100 GeV (Fig. 4) and is well suited as a test beam for a cross calibration between satellite and atmospheric telescopes. A calibration data set with sufficient statistics to use the overlap between VERITAS and GLAST (50 GeV - 300 GeV), requires M 40 days of exposure for the GLAST telescope, providing M 160 photons above 10 GeV. This estimate is based on the energy spectral fit shown in Fig. 4 of Hillas et al. (1998) with a differential spectrum of dN/dE 0: E-2.44-0.1510gloE and collection areas given in the GLAST proposal. We require, that at least lO(2) photons are detected above lOO(300) GeV, providing ample overlap with VERITAS between 50 GeV - 300 GeV. The ground-based instruments, due to their large collection areas (10, 000m2 for VERITAS at 100 GeV) are capable of collecting sufficient statistics on much shorter time scale. A calibration between GLAST and VERITAS could be achieved by normalizing the absolute fluxes to the well calibrated GLAST spectrum by allowing the spectrum of the IACT to shift in energy.d. With the assumed statistics for the GLAST spectrum, the flux normalization would carry a M 15% statistical uncertainty, translating in a 10% accuracy for the absolute energy calibration. The exercise shown here serves exemplary character and a more precise estimate needs to be done in the future. A curved spectrum (see Fig. 4) could also be used to perform a direct energy calibration, independent from the collection area, by measuring the y-ray emission peak for both instruments and determine the offset. The peak emisdThis uses the fact that the collection areas of IACTs can be well calculated using simulations.
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Figure 4. The Whipple and EGRET observations of the Cmb unpulsed ?-myspectrum are shown above (f.om Hillas et al. 1998). The full-line curves are predicted inverse Compton fluxes for three different assumed magnetic fields in the region where the TeV T-mys are produced.
sion for the Crab Nebula seems to occur between 50 GeV - 100 GeV which is well in the range of overlap between GLAST, MAGIC and VERITAS. After a few years of GLAST operation the calibration range could be extended to 1 TeV. This of course needs substantially more statistics and could be considered at a later stage of the GLAST and VERITAS operation. 4. Conclusions
A next generation IACT with a flux sensitivity of a few mCrab and an energy range covering three orders of magnitude (50 GeV -50 TeV) is under development in the northern hemisphere. VERITAS will provide a highly sen-
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sitive view of the high energy universe beyond GeV y-ray energies. VERITAS will complement GLAST, the next generation high energy y-ray instrument in space. GLAST with a wide FOV but small effective area, together with VERITAS with a smaller FOV but large effective area will provide for the first time a continuous coverage for y-ray observations between 20 MeV and 50 TeV. A good absolute energy calibration between northern hemisphere IACTs and GLAST could be achieved using the Crab Nebula spectrum as a test beam. This would enable accurate energy spectral measurements over from MeV TeV energies for astrophysical studies.
Acknowledgments If would like to thank David Carter-Lewis for reading the manuscript. This research is supported by grants from the U.S. Department of Energy. References F.A. Aharonian et al., A&A 349, 11 (1999). J.H. Buckley, et al., 26th ICRC (Salt Lake City) 5 , 267 (1999). J.M. Davies, & E.S. Cotton, J . Solar Energy Sci. and Eng. 1, 16 (1957). D.J. Fegan, J. Phys. G 23, 1013 (1997). 5. N. Gehrels, & P. Michelson, in TeV Astrophysics of extragalactic Sources, Astroparticle Physics 11,277 (1999). 6. R.C. Hartmann et al., ApJS 123, 79 (1999) 7. A.M. Hillas et al., ApJ 503, 744 (1998). 8. A.M. Hillas, Very High Energy Gamma Ray Astronomy, eds. A . A . Stephanian, D.J. Fegan & M.F. Cawley, 134 (1989). 9. W. Hofmann et al., in GeV-TeV Astrophysics: Towards a Major Atmospheric Cherenkov Detector VI (Snowbird), 500 (1999). 10. F. Krennrich et al., ApJ 511, 149 (1999). 11. F. Krennrich et al., ApJL 560, L45 (2001). 12. D.A. Lewis, Exp. Astron. 1, 213 (1990). 13. D.A. Lewis, internal report of Whipple collaboration, (1997). 14. E. Lorenz et al., i n GeV-TeV Astrophysics: Towards a Major Atmospheric Cherenkov Detector V I (Snowbird), 510 (1999). 15. Y. Matsubara et al., in GeV-TeV Astrophysics: Towards a Major Atmospheric Cherenkov Detector V I (Snowbird), 447 (1999). 16. United States Committee on Extension to the Standard Atmosphere US. Standard Atmosphere 1976 in Supt. of Docs., U.S. Govt. Print. Off. (1976). 17. V.V. Vassiliev, et al., 26th ICRC (Salt Lake City) 5,299 (1999). 18. T.C. Weekes, A I P Proc, of the International Symposium on High Energy Gamma-Ray Astronomy (Heidelberg), eds. Aharonian, F.A., Volk, H., 558, 15 1. 2. 3. 4.
(2001). 19. T.C. Weekes et al., Astroparticle Physics 17,221 (2002). 20. T.C. Weekes, ApJ 342, 379 (1989).
PIERRE AUGER OBSERVATORY: THE WORLD’S LARGEST CALORIMETER
A. K. TRIPATHI Department of Physics and Astronomy, University of California Los Angeles, Califronia, USA E-mail: arunOphysics. ucla.edu
The Pierre Auger Observatory is designed to observe and study a high statistics sample of ultra high energy cosmic rays (UHECR) with energy greater than 10’’ eV. The hybrid nature of the observatories, using both air-fluorescence and ground water Cherenkov array, will enable Auger to measure the energy of the cosmic ray showers with an improved accuracy compared to previous experiments. With a surface area of 3000 Km’, and an effective aperture of at least 7350 Km’Sr for each observatory, the P A 0 will be the world’s largest calorimeter to date, and will be able to conclusively determine whether the cosmic ray spectrum extends beyond the GZK cutoff. The Auger detector components, and the status of the observatory are described in this report. N
1. Introduction Observation of Ultra high energy cosmic rays (UHECR) with energies in excess of lo2’ eV poses as yet unanswered fundamental questions about their origin, acceleration mechanism, and propagation through space. The existing experimental data does not conclusively establish the existence or absence of GZK cutoff. The cosmic ray flux measured by AGASAl is inconsistent with those measured by the Fly’s Eye2 and HirRes3 experiments for energies greater than lo2’ eV. One possible source of this discrepancy between the two experiments could be a systematic difference in their energy calibration. AGASA is a ground array, measuring the energy of the cosmic ray showers by sampling the charged particle density at the ground, whereas HiRes is an air fluorescence experiment , measuring the shower energy and longitudinal development by detecting the nitrogen fluorescence light. The sources of systematic errors inherent in these two techniques are entirely different. Only a large hybrid detector can conclusive answer the question of the GZK cutoff. The large size will provide a sufficiently high statistics within a reasonable time period, and the hybrid technique will provides a greater degree of accuracy in the shower energy and composition estimates.
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The Pierre Auger Observatory is such a hybrid detector, employing both ground array and air-fluorescence techniques simultaneously. A subset (-J 10%) of the events observed by the PA0 would be detected both by the ground array and the fluorescence detectors, thus allowing for important cross-calibration of the shower energy. This information then can be used to reconstruct the high statistics data sample obtained from the the surface detectors (because of their 100%duty cycle), enabling Auger to conclusively answer whether cosmic ray flux extends beyond the GZK cutoff. The details of the P A 0 detectors, and the status of the observatory are described below. 2. The Surface Detectors The ground array in the PA0 observatory consists of -1600 water Cherenkov detectors, arranged on a hexagonal grid with 1.5 Km spacing. Figure 1 shows the layout of the southern Auger observatory, currently under construction in Argentina. A schematic of the surface detectors is shown in Figure 2. Each surface detector is a cylindrical plastic water tank, with 3.6 m diameter. The interior of the tanks is lined with diffuse white laminated Tyvek layer. The tanks are filled with purified water to a height of 1.2 m, which corresponds to 3.3 radiation lengths. As a result, electrons and photons deposit most of their energy in the detector. Three PMTs are symmetrically mounted on the top of the tanks, with the photocathode facing vertically down. This arrangement of PMTs gives a uniform response to particles entering the detector at different locations. The PMTs used in the surface detectors are 9-inch diameter Photonis XP1805/D1, a custom made for Auger requirements5 in order to satisfy the requirement of good linearity over the needed large dynamic range of (- 5050000) photoelectrons/25 ns at low operating gain of 2 x lo5. These PMTs are not magnetically shielded in the field, but are oriented in a manner that minimizes the effect of earth’s magnetic field6 on the collection efficiency of photoelectrons in order to achieve good energy resolution. Each surface detector is a fully independent unit, and includes a local solar power supply, a computer, two flash ADCs, a GPS unit, a time tagging board, and a radio7. The PMT signals first go through a 20 MHz filter, and then
-
aThese PMTs will be used in the production version of surface detectors, which make up nearly all of the surface array. The 40 tank engineering array uses three different kinds of PMTs: Hamamatsu R5912, ETL 9353KB, and Photonis XP1802/FLB. These PMTs were already available in the market before the PMTs custom designed for Auger were manufactured.
153
Figure 1. The layout of the southern Auger observatory in Argentina. The small dots indicate the location of the surface detectors, and the four big dots indicate the location of the four fluorescence detectors according to the original design. After a recent review, it was decided to move the central FD to the northern edge of the array (near the top of the figure).
are digitized with a 40 MHz, 10 bit flash ADC (FADC). In order to achieve the needed dynamic range, the PMT base provides two signals: one from the anode (the low-gain channel) and the other from the last dynode, which is amplified using an AD8011 amplifier (the high-gain channel). The two signals are then digitized separately by two 10 bit FADCs, thus providing 15 bits of effective dynamic range. 3. The Air Fluorescence Detectors
The Auger surface detector array will be viewed by four fluorescence detectors (FD)8*9located along the periphery of the array. Each FD consists of 6 telescopes, each with a 30' x 30' field of view. A schematic of an Auger FD telescope is shown in Figure 3. Each telescope has a mirror system to collect and focus the fluorescence light, and a pixelized camera to detect the light emitted from different regions of the shower path. Auger used Schmidt optics, with a spherical mirror of 3.4 m radius. The
154
?-
t
Figure 2.
3.6 m
A schematic view of the Auger surface detectors.
fluorescence light emitted from a shower first passes through a UV transmitting filter which reduces the dark sky noise by a factor of 8, while allowing most of the nitrogen fluorescence light to pass through. A circular diaphragm of 1.7 m diameter, centered on the center of curvature of the spherical mirror, defines the aperture of the telescope. The shape of the camera is a section of a sphere with a radius of 1.743 m, located concentric to the spherical mirror. The light reaching the camera is detected by a hexagonal array of 440 PMTs (Photonis XP3062), which provide 1.5' x 1.5' angular resolution. The details of the FD electronics can be found in Gemmeke et al.''. 4. Communication, DAQ and Triggering
The 1600 surface detectors are separated by 1.5 Km and are spread over distances of up to 50 Km. similarly, the distance between any two fluorescence detectors is also quite large. This makes it prohibitively expensive to connect all the detectors with cables. As a result, Auger relies on radio communication to communicate between the detectors and the central data acquisition building. A detailed description of the the radio communication network is available elsewherell. The details of the Auger trigger and DAQ are also available in references be lo^^^^^^' ,14. 5. Aperture and Event Rates
-
Each observatory, when complete, will cover an area of -3000 Km2, providing an effective aperture of 7350 Km2Sr for cosmic rays with zenith angle less
155
UV Filter, corrector ring Figure 3.
A drawing showing the components of a fluorescence detetcor.
than 60'. If events with zenith angle greater than 60' accepted, the aperture increases by 50%. With the inter-detector spacing of 1.5 Km, the array will be fully efficient for cosmic rays with energy greater than 10'' eV. The fluorescence detectors can only be operated during clear, moon-less nights.This limits their duty factor to 10%. As a result, most of the data will come from the surface detectors, since they can be operated round the clock. Table 1 shows the expected event rates for different energies. Note that the event rates beyond 5 x 1019 eV are estimated assuming AGASA' spectrum.
-
6. Calibration and Energy Resolution The calibration of the surface detectors15 is carried out by through going muons. The calibration of fluorescence detectors, however, must be carried out with an absolutely calibrated light source''. A lidar system17J8 using the laser backscattering method will provide information about the atmospheric attenuation length. The energy resolution in Auger has the following components:
156 Table 1. Expected event rates from the southern Auger observatory. Event rates above 5 x 1019 eV are estimated using AGASA spectrum Energy (eV)
23x 21x 22x 25x 21x 22x
10'8
Surface Detectors
Fluorescence Detectors
(Number of Events)/Year
(Number of Events)/Year
15000
4700
1019
5150
515
1019
1590
159
1019
490
49
1020
103
10
1015
32
3
(1) the MC error due to the uncertainty in the physics interaction models at the energies involved, (2) In the case of surface detectors, shower-to-shower fluctuations, and (4)In the case of fluorescence detectors, contamination from Cherenkov light (both direct and scattered) and (5) any systematic errors in the detector calibration. MC s t ~ d i e s ' ~show ~ ~ ' that the expected RMS energy resolution from surface detectors alone is 12% averaged over all energies, assuming the primary cosmic rays consist of equal numbers of proton and iron. The angular resolution is better than 1.1' for all energies, falling to 0.6O for showers with energy above 1020 eV. In the hybrid mode, the expected energy resolution is approximately 10% and the angular resolution is 0.5% for showers with energies above 1020 eV.
7. Status of Auger The first Auger observatory is under construction near Malargue ( latitude = -35.2', longitude -69.2') in Mendoza Province of Argentina. This site is located at a mean altitude of approximately 1400 m above sea level. The construction of an engineering array of 40 surface detectors and two fluorescence telescopes was completed in the December of 2002. Figure 4 shows the picture of a fully instrumented and functional tank, and Figure 5 shows the prototype FD detectors used in the engineering run. The purpose of this array was to test, debug and optimize all the detector components, communications, and the data acquisition system. This array successfully ran in hybrid mode until the end of March 2002, observing several hybrid showers. The FD telescopes were then dismantled in order t o install the production version, but the surface detectors have been in operation continuously. At the the time of writing of this report, the deployment of new surface and fluorescence detectors is already
157
Figure 4. A picture of a fully instrumented and functional surface detector in the engineering array, currently under operation in Malargue, Argentina. The solar panel, the battery box and the communications antenna are visible.
Figure 5 . Pictures of the prototype FD detector system used in the engineering run. The aperture system and the camera can be seen on the left, and the mirror on the right.
in progress, and the southern observatory is expected to be complete by the end of 2004.
8. Summary Pierre Auger Observatory will be the world’s largest calorimeter to date, utilizing the atmosphere as a giant calorimeter. The hybrid nature of the ob-
158
servatory will allow Auger to measure t h e energy as well as composition of t h e UHECR with a n accuracy not possible before. This, combined with the large aperture, will allow Auger to conclusively settle t h e question of the GZK cutoff, a n d help solve the mystery still surrounding UHECR.
References 1. M. Takeda et al., Phys. Rev. Lett. 81, 1163 (1998). 2. D. J. Bird et al., Phys. Rev. Lett. 71,3401 (1993). 3. C. H. Jui, for the HiRes collaboration, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001); F. Halzen and D. Hooper, submitted
to Rep. Prog. in Phys. (astro-ph/0204527) .
4. M. T. Dova, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 5. A. Tripathi et al., “Tests of New Extended Dynamic Range PMTs for Auger Project”, Pierre Auger Project Technical Note GAP-2001-049, (2001). 6. A. Tripathi, K. Arisaka, T. Ohnuki, and P. Ranin, “Effect of Earth’s Magnetic
Field on Production Photonis PMTs”, Pierre Auger Project Technical Note GAP2002-013, (2002). 7. T. Suomijarvi, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 8. G. Matthiae, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 9. R. Cester, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 10. H. Gemmeke, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 11. P. D. J. Clark and D. Nitz, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 12. D. Nitz, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 13. R. Meyhandan, J. Matthews, D. Nitz, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 14. H. Gemmeke et al., in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 15. H. Salazar, L. Nellen, L. Villasenor, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 16. H. 0. Klages, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 17. A. Filipcic et al., in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 18. J. Matthews and Roger Clay, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 19. M. Ave, J. Lloyd-Evans and A. A. Watson, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001). 20. B. Dawson and P. Sommers, in Proceedings of the 27th International Cosmic Ray Conference, Hamburg, (2001).
Crystal Calorimetry Covener: W. Wisniewski
H.-C. Huang
Performance of a Small Angle BGO Calorimeter at BELLE
M. Kocian
Performance and Calibration of the Crystal Calorimeter of the BaBar Detector
T . Hryn’ova
A Systematic Study of Radiation Damage t o Large Crystals of CsI(T1) in the BaBar
B. A. Shwartz
Performance and Upgrade Plans of the BELLE Calorimeter
Q. Deng
Development of Yttrium Doped Lead Tungstate Crystal for Physics Applications
A. Gasparian
Performance of PWO Crystal Detectors for a High Resolution Hybrid Electromagnetic Calorimeter at Jefferson Lab
R. Novotny
The PHOTON BALL at COSY
*P. Lecomte
Overview of the CMS Electromagnetic Calorimeter
F. Cavallari
Performance of the PWO Crystals of the CMS Electromagnetic Calorimeter
R. Rusack
Avalanche Photodiodes for the CMS Lead Tungstate Calorimeter
E. Auffray
CMS/ECAL Barrel Construction and Quality Control
*Written contribution not received
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PERFORMANCE OF A SMALL ANGLE BGO CALORIMETER AT BELLE
H.-C. HUANG National Taiwan University, Taipei, Taiwan 106, R. 0.C. E-mail:
[email protected] (For the Belle Collaboration)
The Extreme Forward Calorimeter (EFC) at Belle has been operating since the spring of 1999 on KEKB. It consists of 320 radiation-hard BGO crystals surrounding the beam pipe to cover the small angle region in both forward and backward directions. The main function of EFC is to provide on-line luminosity information using Bhabha scattering and it also acts as a tag for two-photon production events. The calorimeter has been performing well and running stably under high luminosity and beam currents. Its performance and status are presented.
1. Introduction
A small angle calorimeter, the Extreme Forward Calorimeter (EFC)' , has been installed last April in the Belle detector1 at the KEKB electron positron collider2. The main functions of EFC are providing the online luminosity information to the detector and accelerator, and acting as a tag for twophoton events. The electromagnetic shower medium is Bismuth Germanate (Bi4Ges012), commonly known as BGO. Since the radiation hardness is an important issue for this device, we choose the radiation-hard BGO crystals3 produced by the Institute of Inorganic Chemistry, Novosibirsk, Russia. Its radiation hardness has been checked to be good after receiving 100 Mrad dose4. EFC consists of two parts, forward and backward, which are mounted on the front surfaces of the cryostats of the compensating solenoids of KEKB. The angular coverage is from 6.4" to 11.5" and from 163.3" to 171.2" for forward and backward, respectively. Each part consists of 160 BGO crystals with 5 segments in 8 and 32 segments in 4.Due to space limitation, the lengths are only 12 and 11 radiation lengths for the forward and the backward BGO crystals.
161
163
The encoded time signals are then fed into a fan-out modules via 60m long twisted pair cables and split into a dual DAQ system, which consists of two almost identical sets of Fastbus and VME crates, called global and local DAQ, separately. The local DAQ is specifically for taking data in parallel with Belle global DAQ without any interference. This is important for monitoring and calibration purpose. The digitization is done with 16-bit multi-hit Fastbus TDCs operated in common-stop mode. The maximum data taking rate for the local DAQ is about 500 Hz. 3. Trigger System
The basic EFC trigger unit is a trigger cell. Two neighboring 4 segments (each segment consists of 5 crystals) of the detector have three trigger cells according to different 8 angles. In the innermost ring, a trigger cell consists of two crystals and its signal is formed by the analog sum of these two channels. The other two trigger cells consist of four crystals. The trigger output of each cell is generated by the CFD circuit in the receiver module. Currently the 2 GeV for the forward and 1 GeV for the trigger thresholds are set to backward. These trigger output are then grouped into four sectors in I$ with a logical OR in the forward and the backward, respectively. A typical trigger rate of cm-2s-1. one sector is around 50 Hz at instantaneous luminosity of The Bhabha trigger is defined by a back-to-back coincidence of energetic electromagnetic showers. Besides being used for the global DAQ and local DAQ, the Bhabha trigger signal is also sent to a CAMAC scalar for on-line luminosity measurement. To make a reliable measurement of luminosity, one has to subtract the accidental rate of the Bhabha trigger. A logic is made by geometrically wrong combinations (not back-to-back) of trigger sectors to estimate such fake rate. The typical fake rate is less than O.1Hz under normal beam condition. The EFC-Tag trigger is defined as a logical OR of all the forward trigger sectors. Currently, two kinds of tagged two-photon triggers are implemented in Belle data taking. One is defined as EFC-Tag A N D “at least one full charged track”; the other is EFC-Tag A N D “at least one electromagnetic cluster”. Each one gives a trigger rate of around 2 Hz at instantaneous luminosity of 1033~m-2s-1. N
-
4. Calibration
Bhabha events are used to calibrate the EFC detector. Considering the boost effect of asymmetric collision at KEKB, only inner 2 layers of forward EFC and
164
outer 3 layers of backward EFC can make coincidence to form the back-to-back Bhabha trigger and to accumulate Bhabha events. However, based on Monte Carlo (MC) study, and the rates from Bhabha trigger and ALL-OR trigger, the Bhabha scattering contribute 73% (83%)of the forward (backward) ALL-OR trigger rate. Other processes like Coulomb scattering, bremsstrahlung,twophoton and beam gas interaction are less important. Therefore, we took EFC “forward All-OR” and “backward ALL-OR” two different data sets by local DAQ to calibrate EFC. The calibration is done by minimizing the difference between the expected shower energy and the measured energy by EFC. The x2 is determined by
”
i= 1
where Eezpis 6 GeV (3 GeV) for the forward (backward) EFC Bhabha clusters, N is the total number of events, g j is the calibration constant, and the Ej is the measured energy in the j-th crystal in the 3 x 3 matrix cluster. Figure 2 shows the energy distribution of Bhabha data collected by EFC. We use a Bifurcated Gaussian function to fit the energy distribution and the tail at the left side of the peak is due to the energy leak. The Bifurcated Gaussian resolutions of Bhabha events are 14.8% (left a ) and 8.6% (righ at) for the forward EFC and 16.1% (lef a t ) and 10.4% (right a ) for backward EFC, as shown in Fig. 2.
Energy Spectrum of EFC Bhabha 350 300
250 200 150 100
50 0
0
2
4
6
E FEFC
8
10
0
1
2
3
4
5
E BEFC
Figure 2. The energy spectra of Bhabha events detected by EFC in the forward (left) and the backward (right).
165 5. Luminosity Measurement
In the e+e- collider, the luminosity can be determined by measuring the known QED process such as e+e- -+ e+e-(y) (Bhabha scattering). EFC is able to provide the instantaneous luminosity measurement by counting the event rate of Bhabha scattering. As described in Sec. 3, we use the fake rate subtracted back-to-back coincidence rate multiplies a conversion factor to obtain the luminosity, C = factor x (Bhabha rate - fake rate). The conversion factor is in the unit of cm-2s-1 and obtained from the MC according to the trigger geometry and energy threshold. The typical Bhabha cm-2s-1 luminosity. rate in the experiment is 140 Hz with 5 . 1 . IP Dependence
The largest systematics of luminosity measurement comes from the movement of interaction point (IP) of KEKB. Due to the small distance between EFC and IP, the IP position change on z axis affects the acceptance of Bhabha scattering. The MC shows the IP-dependent acceptance of EFC Bhabha measurement, as shown in Fig. 3. A linear correlation is found between the acceptance and IP position in z axis. We also see the same relation when we compare the ratio of EFC over the central electromagnetic calorimeter (ECL) luminosity measurement, as shown in Fig. 4. The luminosity ratio shows fluctuation during the experiment runs. After applying the corrections obtained by MC, the ratio of EFC over ECL remains stable during the experiment. 6. Two-photon Physics
The EFC-tag trigger described in Sec. 3 records the two-photon processes in which one of the re-scattered electrons hits EFC. The momentum transfer, q, of the corresponding photon can be measured by the energy deposit in EFC of that re-scattered electron and its position. From the EFC energy and angular resolution, we can estimate the Q2 resolution of the forward EFC for tagged two photon events. The Q2 of the forward EFC tagged data can be extracted by Q2 = -q2 = 2EE'(1 - cosB'), where the E' is the tagged electron energy, and 6'' is the tagged electron angle. The Q 2 range of the forward EFC tagged two photon process is between 0.2 GeV to 2.5 GeV. R o m the EFC angular and energy resolution, the expected Q2 resolution is 9.5%.
7. Summary EFC has been operated since 1999 and providing stable luminosity measurement for KEKB. The performance of energy resolution and stability of lumi-
166
-
Exp 13 Run 1 1500
-
MC IPI effect on EFC Bhabha
g
,
1 j:. .
:
. L: .....
i
.
. I
:
j
.
L.......
i
:
:
J:
j
: :
1
:
^I
1
1
IP in z (mm)
Figure 3. The EFC Bhabha acceptance versus IP-z positions. A linear correlation is observed in MC.
Figure 4. The luminosity ratio of EFC over ECL, IP position in z-axis, and corrected luminosity ratio.
nosity are reported. EFC can also give correct Q2 estimation for triggered two-photon events and make certain QCD studies feasible.
Acknowledgments I would like to thank the CALOR2002 organization committee t o host such a wonderful conference. I would also like to thank Rong-Shyang Lu and ChinChi Wang who help me operate and maintain EFC at KEK. This work is supported by the National Science Council and the Ministry of Education of Taiwan. References 1. Belle Collaboration, A. Abashian et al., Nucl. Inst. and Meth. A479, 117 (2002). 2. E. Kikutani ed., KEK Preprint 2001-157, t o appear in Nucl. Inst. and Meth. A . 3. Ya. V. Vasiliev et al., Nucl. Inst. and Meth. A379, 533 (1996). 4. K.C. Peng et al., Nucl. Inst. and Meth. A 4 2 7 , 524 (1999). 5. K. Ueno et al., Nucl. Inst. and Meth. A396, 103 (1997).
PERFORMANCE AND CALIBRATION OF THE CRYSTAL CALORIMETER OF THE BABAR DETECTOR
M. KOCIAN SLAC, M S 61, 2575 Sand Hill Rd.,Menlo Park, CA 94025, USA E-mail: kocianOslac.stanford.edu (for the B A B A R calorimeter group) The BABAR detector at the B-factory at SLAC is equipped with a calorimeter consisting of 6580 CsI(T1) crystals. This allows for the measurement of the energies of photons and neutral pions and the identification of electrons with high precision, needed in the reconstruction of B-meson decays. The detailed performance of the calorimeter will he presented. As the B-factory operates at high luminosity the calorimeter is exposed to substantial background and radiation damage. The calorimeter is calibrated regularly at different energies in order to meet the precision goals. The calibration methods include the use of a radioactive source, Bhabha events, radiative Bhahha events, 7ro-Mesons, and a light pulser system. This article largely follows reference'.
1. Introduction
BABAR is the detector at the PEP-I1 B Factory at SLAC. PEP-I1 is an asymmetric e+e--collider, currently operating at a luminosity of 4.5 x cm-2s-1 at a center-of-mass energy of 10.58 GeV, the mass of the Y(4S) resonance. The Y(4S) decays exclusively into BOBo and B+B- pairs. The main physics goal of BABAR is the study of CP-violating asymmetries in the decay of neutral B-mesons. Secondary goals are precision measurements of decays of bottom and charm mesons and of T leptons, and searches for rare processes that become accessible with the high luminosity of the PEP-I1 B Factory. The BABAR detector consists of 6 subdetectors. F'rom the inside to the outside, there is a Silicon Vertex Detector, a Drift Chamber, a DIRC (Cherenkov- Detector), an Electromagnetic Calorimeter, and an Instrumented Flux Return (fig. 1). 2. Calorimetry goals
The very small branching ratios of B mesons to C P eigenstates and the need for full reconstruction of final states with several r o s place stringent requirements
167
168
IFR Barrel
0
I
' scale ' 4m BABAR Coordinate System
8583A51
Figure 1. The components of the B A B A R detector
on the electromagnetic calorimeter: a large and uniform acceptance down to small polar angles relative t o the boost direction excellent reconstruction efficiency for photons down to 20 MeV energy resolution of order 1- 2 % and excellent angular resolution for the detection of photons from AO and decays in the range from 20 MeV to 4 GeV efficient electron identification with low misidentification probabilities for hadrons.
For these reasons the choice for BABAR was a CsI(T1) crystal calorimeter. The energy resolution of a homogeneous crystal calorimeter can be described empirically in terms of a sum of two terms added in quadrature (1)
where E and UE refer to the energy of a photon and its rms error, measured in GeV. The energy dependent term a arises from fluctuations in photon statistics,
169
electronics noise and beam background noise. The constant term b is dominant at higher energies and arises from non-uniformity in light collection, shower leakage or absorption in the material between and in front of the crystals, and uncertainties in calibration. The angular resolution is determined from the transverse crystal size and the distance from the interaction point. It is parametrized as
The actual resolution for the BABAR calorimeter will be discussed in section 5.2.
3. Layout and Assembly 3.1. General Overview
Interaction Point Figure 2.
1979
8572A03
A longitudinal cross-section of the Calorimeter
The calorimeter consists of 6580 CsI(T1) crystals. Its angular coverage is 126' in polar angle and 360" in azimuthal angle (see fig. 2). It is subdivided into a barrel and a forward endcap. The barrel consists of 5760 crystals arranged in 48 rings of 120 crystals, while the endcap contains 8 rings. The innermost 2 rings contain 80 crystals, the next three rings 100, and the three outer rings 120 crystals. The calorimeter's geometry is projective in 4, while in 0 there is a non-projectivity of 14 mrad, except in the transition region between barrel and endcap where it reaches 45 mrad. The non-projectivity minimizes the
170
energy losses through the spaces between the crystals. There is a gap of about 2 mm between the barrel and the endcap which is fully covered by the higher non-projectivity in this region.
3.2. Mechanical Assembly The individual crystals are assembled in carbon fiber modules. In the barrel, the modules contain 7 x 3 crystals (except for the most backward module which only contains 6 x 3 crystals). The entire barrel consists of 280 carbon fiber modules. In the endcap, each carbon fiber module contains 41 crystals. The carbon fiber housings are glued onto Aluminum strongbacks. The barrel modules are inserted into an Aluminum cylinder. The endcap modules are held in place by two semicircular structures. 3.3. Crystal Assembly The crystals are trapezoidal in shape. The typical area of the front face is 4.7 x 4.7 cm’, while the back face area is typically 6.1 x 6.0 cm’. The length of the crystals varies between 16 radiation lengths in the backward part and 17.5 radiation lengths in the forward part. The polished crystals are wrapped in two layers of Tyvek (2 x 165 pm) for reflection and tuning. The next layers are Aluminum foil (25 pm) and Mylar (13 pm) for electrical insulation (fig. 3). The outside layer is a 300 pm thick carbon fiber housing which is attached to the housings of the neighbour crystals. The crystals are read out through 2 silicon PIN photodiodes of 2 x 1 cm’ area each. The diodes are glued onto a polystyrene coupling plate which itself is glued onto the crystal with transparent epoxy. The area surrounding the diodes is covered with white, painted plastic plates to reflect light. Each diode is read out by a preamplifier that sits in a housing above the crystal. For the details of the electronics readout see reference’. 4. Calibration
4.1. Overview The energy calibration of the calorimeter proceeds in two steps. First, the measured pulse height in each crystal has to be transformed into the deposited energy. Second, the deposited energy in a shower has to be related to the energy of the incident photon or electron by correcting for energy loss mostly due to leakage and absorption in material between and in front of the crystals. Table 1 shows a summary of the calibrations used for the BABAR calorimeter. The electronics and light pulser calibrations are discussed in reference2.
171
Figure 3.
A schematic of the wrapped crystal
Table 1. Properties of the different calibrations for the calorimeter. “Absolute” refers to the ability to tie the measurement t o an absolute energy scale as opposed t o measuring the relative changes and differences in signal height.
Source
Duration
Energy Scale
Single Crystal
Absolute
20 min
0.00613 GeV
Yes
Yes
3-9 GeV
No
Yes
4h
0.03 - 3 GeV
No
Yes
Yes
No
Yes
No
Bhabha
0 - 13 GeV
I Light Pulser I
3 min
0 - 13 GeV
i I ~
172
4.2. Individual Crystal Calibration
In spite of the careful selection and tuning of the crystals, their light yield varies significantly and is non-uniform along the crystal axis. It also changes with time under the impact of beam-generated radiation. The absorbed dose is largest at the front of the crystal and results in increased attenuation of the transmitted scintillation light. The light yield must therefore be calibrated at different energies, corresponding to different average shower penetration, to account for the effects of the radiation damage3. The calibration of the deposited energies is performed at two energies at opposite ends of the dynamic range, and these two measurements are combined by a logarithmic interpolation. A 6.13 MeV radioactive photon source provides an absolute calibration at low energy, while at higher energies the relation between polar angle and energy in Bhabha events is used for calibration.
4.2.1. Radioactive Source Calibration The radioactive source calibration uses 6.13 MeV photons produced in the reaction
+ n +16
N
+ a,16N
+16
O* + p,16 O* +16
o + y.
(3)
16N has a lifetime of 7 seconds. A fluid of polychlorotrifluoro-ethylene, activated by neutrons from a generator, circulates through a system of tubes in front of the crystals. All crystals in the calorimeter are calibrated with this method. The average resolution for the constants is 0.33 %.
4.2.2. The Bhabha Calibration At high energies, single crystal calibration is performed with a pure sample of Bhabha events. As a function of the polar angle of the e*, the deposited cluster energy is constrained to equal the prediction of a GEANT based Monte Carlo simulation. For a large number of energy clusters, a set of simulates linear equations relates the measured to the expected energy and thus permits the determination of a constant for each crystal. 200 e* per crystal result in constants with a statistical error of 0.35 %.
4.3. Shower Energy Correction The correction for energy loss due to shower leakage and absorption is performed as a function of shower energy and polar angle. For low energies it is derived from 7ro decays, while for high energies corrections derived from single photon Monte Carlo or from radiative Bhabha events can be used.
173
4.3.1.
TO
Calibration
For the no calibration the energy range is subdivided into 16 bins in ln(E), while the angular range is divided into 9 bins in cos(8). For each bin a twophoton-mass plot is generated. By constraining the peaks to the nominal mass, a correction polynomial of third order in ln(E) and a correction polynomial of second order in cos(8) are determined in an iterative procedure. Typical corrections are of order 6 f 1 %. 5 . Performance
5.1.
d' and
77 mass and width
Figure 4a shows the two-photon invariant mass for hadronic events around the T O mass in data from 2001. Photons are required to exceed 30 MeV, while 7ro exceed 300 MeV. The reconstructed mass is measured t o be 134.9 MeV/c2. The width is 6.5 MeV/c2. The two-photon-invariant mass for symmetric 77s for Ev > 1 GeV is shown in figure 4b. The reconstructed mass is 547 MeV/c2, the width is 15.5 MeV/c2.
Figure 4. data.
Invariant mass of two photons in hadronic events. The solid lines are fits t o the
5 . 2 . Resolution
Figure 5a shows the energy resolution derived from a variety of processes: radioactive source, symmetric T O and 17 decays, xcl + J/y!ry, and Bhabha events. As the resolution of T O and 17 depends on the angular resolution also, a simultaneous fit to energy and angular resolution was done for those cases, assuming an asymmetry of the photon energy distribution derived from Monte Carlo. There is good agreement between the measured resolution and Monte
A SYSTEMATIC STUDY OF RADIATION DAMAGE TO LARGE CRYSTALS OF CSI(TL) IN THE BABAR DETECTOR
T. HRYN'OVA SLAG, MS 61, 2575 Sand Hill Rd., Menlo Park, C A , USA E-mail:
[email protected] (For the BaBar EMC Group) We study the impact of radiation damage on large CsI(T1) crystals in the BABAR electromagnetic calorimeter. Average radiation exposure of up to 400 Rad to date, originating primarily from beam backgrounds, has been measured by RadFETs located at the front face of crystals.
1. Introduction
The BABAR Electromagnetic Calorimeter' (EMC) consists of 6580 CsI(T1) crystals ranging between 16 and 17.5 radiation lengths. CsI(T1) was chosen for its good mechanical properties, high light output, convenient emission wavelength for use with Si-photodiodes and reasonable signal response time. The crystals were produced2 from a melt of CsI salt doped with 0.1%thalium using either Kyropoulos (Kharkov, Crismatec, Hilger) or Bridgman (Shanghai, Beijing) growth techniques. As sensitivity to radiation damage is generally found to be smaller for higher purity crystal, the quality of the salt and the recycled material was strictly controlled. In order to decrease the contributions to systematic errors on energy resolution it is important to understand the effect of radiation on CsI(T1) crystals. 2. Sources of Radiation Damage
Radiation damage in the BABAR EMC is believed3 t o be almost entirely caused by 'non-physics' events, or so called 'beam backgrounds' in the EMC. There are two distinct types of this background in the BABAR experiment: single beam background and colliding beam background. The single beam background is mainly caused by fixed dipole magnets which are situated near the interaction point. They tend to sweep off-energy primary beam particles into machine elements near the detector, resulting in a low-energy shower (
At ~ *the . emission peak, 420 nm, the transmittance of the extraordinary polarized light is about 3% higher than that of the ordinary light. The PbW04 specification on the transmittance, aiming at setting a limit on the internal absorption, thus is crystal orientation dependent, i.e. the transmittance specification along the c axis should be lower than that along the direction perpendicular to the c axis to allow the same density of absorption centers. Since PbW04 crystals are grown along the c axis at SIC, the difference between the longitudinal and transverse transmittance shown in Figures 7 reflects the internal absorption integrated over the light path as well as the birefringence. It is also interesting to note that the transverse transmittance curves measured in two directions perpendicular t o the c axis at both the seed and tail ends are almost identical, indicating that (1) PbW04 crystals grown along the c axis is isotropic transversely and (2) this sample has very good longitudinal uniformity. Figure 8 shows the longitudinal transmittance as a function of wavelength for three PbWO4 samples produced at different time. Also shown in the figure is the theoretical limit of transmittance along the c axis. As seen from the figure that recent grown crystals approach theoretical limit, indicating very low residual absorption. Early samples have a low transmittance at short wavelength caused by scattering centers, but no direct correlations between
80
1
SIC-U517 80
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-
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.
e 6 0 -
.-Seed end transverse (x.y) :.--. Tail end transverse (x,y) - Longitudinal (z)
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Calculated transmittance 0 /I c axis, 0
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I c axis, unpolarized11 ht Ic axis, 6-polarized Ii&t
'
'
'6h
'
'
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'
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Wavelength (nm) Figure 7. Transverse and longitudinal transmittance of sample U517.
o Theoretical c-axis limit From top to bottom
U517,12/2001 S762,12/1999 s643,11/1999
20 -
u
900
400
500
600
700
t
0
Wavelength (nm) Figure 8. Progress of longitudinal trans&tame of three PbW04 samples.
197 40
J 1999
Transmission at 360 nm (%)
Transmission at 360 nm (%)
Transmission at 360 nm (%)
Transmission at 360 nm (%)
Figure 9.
Progress of longitudinal transmittance at 360 nm.
transmittance and the radiation hardness were observed. A fine tuning of growth parameters improved transmittance at short wavelength, as shown in Figure 8 and 9, where statistical distribution of longitudinal transmittance at 360 nm is presented for crystals grown in 1999 to 2002.
3.3. Light Output and Decay Kinetics
Full size (25 radiation lengths) yttrium doped PbW04 crystals produces typically 10 p.e. per MeV energy deposition. It has also a -2%/"C temperature dependence. Stringent control of temperature and its correction are thus necessary to achieve 1% precision in light output measurement15. Figures 10 shows light output as a function of integrated time for three yttrium doped PbW04 samples. Data in these plots are in units of number of photo electrons per MeV of energy deposition (p.e./MeV). The ratio between light outputs integrated to 100 and 1,000 ns is about 95%, as compared to 90% and 85% for Sb doped and undoped PbW04 crystals re~pectively'~.
198 11
SIC-S347 lo-
SIC-S392
c
,
L 0 = 8 4 pelMeV
(mn6.20 0%)
+ ++
t + + + +
++
t+
+ tttt
dose rate (,a&): 5
Gale(ns) Omdh
0
"
"
50 89
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XK)
100
98 ~
'
2oM)
"
2MK)
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15
105
104 '
'
'
'
4ow
Time (ns) Figure 10. Light output is shown as a function of integration time for three samples.
0.7
'
,
,
+
loo
+Em
,I M O ,
,
1W
200
3w
400
Time (hours) Figure 11. Normalized light output is shown as a function of time under irradiations for sample S392.
3.4. Light Output Degradation under Irradiation
The light output, however, degrades under irradiation. It is known that radiation induced color centers are created in PbW04 crystals by irradiation, and may annihilate in room temperature. During irradiation, both annihilation and creation processes coexist, the color center density reaches an equilibrium at a level depending on the dose rate applied6. Figures 11 shows light output normalized to that before irradiation (solid dots with error bars) as a function of time under irradiation for sample S392. The light output was defined as an average of nine measurements with a collimated 13'Cs source shooting at evenly distributed positions along the sample to properly evaluate the degradation of light output and reduce systematic uncertainty. Measurements were done step by step for different dose rates: 15, 100, 500 and 1,000 rad/h, as shown in these figures. The degradation of the light output shows a clear dose rate dependence, as described in reference6. Table 3 summarizes the numerical results of the light output before irradiation and the normalized light output (%) in equilibrium under certain dose rates. The light output (L.O.), in units of number of photoelectrons per MeV energy deposit (p.e./MeV), is defined as the average of nine measurements with an integration time of 200 ns at 2O.O0C. By using emission weighted quantum efficiencies of the R2059 P M T (14.8%), the measured light output was converted to the light yield in units of photons/MeV.
199 Table 3. Sample ID S301 S347 S392 S412 S643 S762 606 678 679 L411 U517 LS614 LS615 U685 U686 U688 U689 U690 U691 U692
Summary of light output measurements
L.O. (l/MeV) P.e. 9.4 9.9 8.4 8.3 8.9 10.6 10.4 10.4 10.8 11.7 10.3 8.6 9.9 11.4 10.8 11.1 10.4 12.3 10.8 10.5
Y 63.5 66.9 56.8 56.1 60.1 71.6 70.3 70.3 73.0 79.1 69.6 58.2 66.9 81.4 77.1 79.3 74.3 87.9 77.1 75.0
L.O.(%)@R(rad/h) 100 500 1000
Fraction(%) 50ns _ _ loons lps
lps
15
92.0 91.3 92.0 94.6 88.8 85.6 88.3 85.2 85.0 71.8 70.8 87.2 82.8 91.3 92.1 90.5 92.6 90.1 91.8 92.0
96.6 97.8 97.3 98.6 98.9 94.2 98.4 93.5 94.7 94.0 93.2 97.6 96.9 97.9 97.5 95.5 96.3 96.5 97.7 98.5
96.6 95.1 98.2 98.2 88.3 91.5 91.7 94.2 93.5 88.3 87.0 98.1 89.7 90.4 98.5 91.9 95.5 92.7 94.7 93.2
87.3 88.6 91.3 91.2 79.8 84.2 79.3 76.0 73.5 79.2 71.6 89.5 80.9
79.5 82.1 83.6 85.9
74.3 78.0 80.2 85.3
-
-
81.4
-
-
59.6 57.3 72.3 62.7 84.6 76.1
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
3.5. Damage Recovery
The radiation damage in PbW04 crystal recovers at room temperature. Since the light output of PbW04 crystals varies during both damage and recovery, a precision calibration is the key for maintaining the precision of crystal calorimetry in s i k . For CMS PbW04 calorimeter the calibration is achieved by using various physics while variations of the calibration caused by radiation damage and recovery are traced by a light monitoring system, which measures transmittance to 0.1% at the peak wavelength of PbW04 emission2'. Since a complete monitoring run for entire calorimeter takes about 37 minutes, the variation speed for the light output, either during damage or during recovery, is preferred to be less than l%/h. Figure 12 shows the damage (dots with error bars, left scale), corresponding exponential fit (solid lines) and damage speed (dashed lines, right scale) of normalized light output under irradiation at 15 rad/h for sample S392. Figure 13 shows the recovery (dots with error bars, left scale), corresponding exponential fit (solid line) and recovery speed (dashed lines, right scale) of normalized light output after an irradiation at 400 rad/h for sample S392. While the damage data were fit to
200 11
0 1
SICS392 Dose rate 15 rad%
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0.8
SIC-S392 Alle~400 ram in Equilibrium
.
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Tirne(hours)
Time (hours)
Figure 12. Light output damage (dots with error bars, left scale) and damage speed (dashed lines, right scale) for sample S392.
Figure 13. Light output recovery (dots with error bars, left scale) and recovery speed (dashed lines, right scale) for sample S392.
Table 4. (Wh) Sample ID 5301 S347 S392 S412 S643 S762 606 678 679
Summary of PbW04 damage and recovery speed Damage - under (rad/h) . . . 15 100 400 1,000 -0.21 -2.3 -4.9 -0.35 -3.9 -0.28 -0.67 -0.54 -0.23 -1.3 -1.6 -0.04 -0.81 -0.10 -0.82 -1.7 -0.85 -1.4 -1.0 -3.6 -3.0 -1.9 -0.31 -0.53 -3.1 -9.0 -5.3 -1.1 -5.8 -0.21 -4.8
Recovery from 400 rad/h 0.37 0.27 0.31 0.19 0.41 0.04 0.48 0.59 0.41
the recovery data were fit to
LY/LYo = 1 - a - beFt/' = (1 - a - b) + b( 1 - e - t / T ) ,
(6)
where a and b are two constants representing the amplitude of the slow and fast components respectively, and r is the time constant of the fast component. Table 4 lists the maximum speed (in units of %/h) of light output variation for the damage process under different dose rates and for the recovery process after reaching equilibrium at 400 rad/h. As shown in the table, some samples may have too fast damage speed under irradiation, indicating possible less accurate calibrations for a short time at the beginning.
201
3.6. Light Response Uniformity
While variations of the amplitude of the light output can be inter calibrated, the loss of the energy resolution, caused by the degradation of light response uniformity is not recoverable3. To preserve crystal's intrinsic energy resolution the light response uniformity thus must be kept within tolerance. The light response uniformity was measured by moving a collimated y-ray source along the longitudinal axis of the sample at nine points evenly distributed along the crystal and the response (y) was fit to a linear function,
JL = 1 + 6 ( X / X m i *
- l),
(7)
Ymid
where ymid represents the light response at the middle of the crystal, 6 represents the deviation of the light response uniformity, and x is the distance from the small (front) end of a tapered crystal. Figures 14 shows the light response uniformity as a function of accumulated dose for samples S412, where 6 is a measure of the light response uniformity, as defined in equation 7. These figures show clearly that the slope ( 6 ) and the shape of the uniformity does not change. This good uniformity can be attributed to the fact that the light attenuation length at the emission peak (420 nm) is long enough even after irradiation, so provides an adequate compensation between the attenuation and the focusing effect caused by crystal's tapered shape3. SIC-S412 I
-
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181
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230
Distance From the Front End of Cfystal (mm)
Figure 14. The light response uniformities are shown as a function of integrated dose for sample S412.
1.5
2
2.5
3
3.5
4
Photon Energy (eV)
Figure 15. Radiation induced color center density for sample S392.
202
3.7. Radiation Induced Color Centers The longitudinal transmittance data can be used to calculate radiation induced color center density. Figures 15 shows radiation induced color center density as function of photon energy measured for sample S392 in equilibrium at different dose rates. The stars in these figures represent corresponding radio luminescence spectra weighted with quantum efficiency of the PMT. The points with error bars in these figures are radiation induced color center density (D), or absorption coefficient, measured in equilibrium under dose rates specified. They were calculated according to an equation
D
= 1/LALeguilibrizLrn - 1 / L A L b e f o r e .
(8)
where LAL is light attenuation length calculated by using longitudinal transmittance according to Equation 1 of reference17, and the subscript “equilibrium” and “before” refer to “in equilibrium” and “before irradiation” respectively. The radiation induced color center density was decomposed to a sum (solid line) of two color centers with Gaussian shape in photon energy (dashed lines) :
i= 1
where Ei, C T ~and Ai denote the energy, width and amplitude of the color center i, and E is photon energy. As seen from these figures, the two center Gaussian fit provides a rather good description of the radiation induced color center data with good X2/DoF.
Table 5.
Summary of radiation induced color centers
A! AT A$ Ez/uz m-’ m-1 eV/eV 5301 0.04 0.07 0.11 3.07/0.76 S347 0.00 0.03 0.07 3.07/0.76 5392 0.04 0.06 0.10 3.07/0.76 0.03 0.04 0.06 3.07/0.76 5412 0.05 0.08 3.07/0.76 S643 0.00 0.00 3.07/0.76 S762 0.07 3.07/0.76 0.14 606 678 0.11 0.23 3.07/0.76 679 0.14 0.26 3.07/0.76 L411 0.08 0.10 3.07/0.76 U517 0.09 0.10 3.07/0.76 LS615 0.07 0.07 3.07/0.76 a , b , c , d represent 15, 100, 500, 1000 rad/h respectively. ID
Ei/u1 eV/eV 2.30/0.19 2.30/0.19 2.30/0.19 2.30/0.19 2.30/0.19 2.30/0.19 2.30/0.19 2.30/0.19 2.30/0.19 2.30/0.19 2.30’/0.19 2.30/0.19
A:
rn-l 0.00 0.00 0.00 0.00 0.02 0.00 0.00 0.03 0.05 0.01 0.01 0.02
~
A; m-l 0.10 0.10 0.10 0.10 0.14 0.11 0.10 0.10 0.10 0.13 0.17 0.13
A;
AC, m-’
0.22 0.13 0.18 0.15 0.22 0.21 0.26 0.38 0.39 0.43 0.47 0.27
0.35 0.14 0.29 0.19 0.25 0.24 0.54 0.78 0.77 0.54 0.48 0.29
A$ m-l 0.42 0.38 0.37 0.24 -
203
Table 5 lists numerical results of fits for yttrium doped PbW04 samples. Consistent fit with two common radiation induced color centers at the same energy and with the same width was found for all samples. One broad center is at wavelength of 400 nm (3.07 eV) with a width of 0.76 eV, and other narrow center is at a longer wavelength of 540 nm (2.30 eV) with a width of 0.19 eV. This observation is similar to what observed in doped BGO samples21, where three common radiation induced absorption bands were observed for BGO samples doped with different dopants, indicating that the radiation induced color centers are presumably not impurity specific rather lattice structure related. This observation also consists with our previous a s ~ u r n p t i o nthat ~~ the oxygen vacancies, which are lattice structure defects, are responsible for radiation damage in PbW04 crystals. 3.8. Stability
One peculiar property was found in yttrium doped PbW04 samples in early development stage. The light output of some yttrium doped samples was found to increase under irradiations. Figure 16 shows the variation of the light output of an early sample after various irradiation and annealing processes. As shown in the figure, its light output was increased by 12% under irradiation a t 15 rad/h, and was increased further after a thermal annealing at 100°C. It was decreased by 10% after a thermal annealing at 200°C. It was also observed that the variations of the light output of these samples correspond to the variations 12
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Figure 17. Samples investigated in hunting Figure 16. Normalized light output after for the origin of the "instability". various irradiation and annealing processes for an early sample.
204
of their transmittance. While showing good light output under irradiations, crystals of this type are not conventional since it is difficult to define their nominal light output. This peculiarity was understood as the effect of pre-existing color center in early crystals shown in Figure 8, and corresponding self optical bleaching by scintillation light, similar to the BaF2 crystal case discussed in reference23. Scintillation light was produced when sample is under irradiation by 6oCo yrays. If the annihilation speed of a pre-existing color center, caused by the bleaching effect of the scintillation light, is larger than the creation speed of a radiation-induced color center under low dose irradiation, the total density of color centers would decrease, not increase, under irradiation6. High temperature annealing also creates such pre-existing centers. A study of optical bleaching by using light of different wavelengths confirmed that the optical bleaching is indeed effective in removing pre-existing color centers. Although an initial thermal annealing at a lower temperature would bypass this problem, R&D was carried out to hunt for the origin of these pre-existing color centers. In this investigation, full size PbW04 ingots were cut into short pieces. As shown in Figure 17, five 2.5 x 2.5 x 4.4 cm samples were cut from ingot 4-1-20, and an 18 and a 5 cm long samples were cut from another full 1.2L
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100
120
140
180
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100
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Time (hours) Figure 18. Normalized light output under irradiation at 1.8 rad/h for five 4.4 cm samples cut from ingot 4-1-20.
125
150
1 5
Time (hours) Figure 19. Normalized light output under irradiation at 4 rad/h for 18 and 5 cm samples cut from ingot B13.
205
size tapered sample B13. All these samples went through standard radiation test at Caltech. It was found that only the sample at the tail end have this problem. Figures 18 and 19 show normalized light output of these short samples under irradiations at low dose rate. No “instability” was found for samples cut from the seed side of ingots. As shown in Table 1 in Section 2, the GDMS analysis revealed that the impurities of Na, K , Cu, As and Mo were concentrated at the tail end15. Following this investigation, several ionic impurities were deliberately added to PbW04 melt to study the consequence. The result shows that monovalant impurities, such as K+ and Na+, enhance pre-existing color center at 420 nm, as shown in Figure 20.
350
400
150
500
550
600
650
700
750
Wavelength (nrn)
Figure 20. Radiation induced absorption of yttrium, potassium and sodium doped PbW04 samples.
Figure 21. Normalized light output loss after irradiation at 35 rad/h.
As a consequence of this study, limitations t o the monovalant impurities were added to the the raw material specification and parameters of crystal growth were modified accordingly. The yttrium doped samples grown at SIC since then are free from this “instability”. Figure21 shows a statistical distribution of the light output loss after irradiation at 35 rad/h measured at SIC. No increase of light output was observed. This observation was also confirmed by measurement at Caltech. Correspondingly, the transmittance at 420 nm has also improved, as shown in Figure 22. 4. Summary
Yttrium doping is found to shift the emission to blue, and yttrium doped PbW04 crystal has a broad spectrum peaked at 420 nm. It is also effective in reducing slow scintillation component, and leading to PbW04 crystals with adequate radiation hardness for the LHC environment. With yttrium doping
206 21
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Transmission at 420 nm (%)
Transmission at420 nm (%)
Transmission at 420 nm (%)
Figure 22.
66
66
70
Progress of longitudinal transmittance at 420 nm.
it is not necessary to implement oxygen compensation. The concentration of yttrium ions in PbW04 crystals is rather uniform with a segregation coefficient of 0.91 f 0.04. The radiation induced absorption in all samples can be decomposed t o two color centers with two common centers peaked at wavelength of 400 nm (3.07 eV) and 540 nm (2.30 eV) with widths of 0.76 and 0.19 eV respectively. These centers are not as deep as that in Sb doped ~arnples’~. This explains a relatively large dose rate dependence of radiation damage and relatively large damage speed in yttrium doped PbW04 crystals. Light output of early yttrium doped PbW04 samples is sensitive to the temperature of thermal annealing. Pre-existing color centers, which are bleachable by scintillation light, led to the “instability”, i.e. the light output increase under irradiations. These pre-existing color centers were found to be caused by impurities at the tail end of ingots, and were formed by contamination of monovalant impurities, such as Na+ and K+. With refined growth parameters and stringent requirement to the purity of raw material these pre-existing color centers were eliminated, so that yttrium doped samples grown recently at SIC are free from the “instability”.
207
Acknowledgments This work is supported in part by U.S. Department of Energy Grant No. DEFG03-92-ER40701.
References 1. Compact Muon Solenoid Technical Proposal, CERN/LHCC LHCC/Pl (1994). 2. A. Gasparian, in these Proceedings. 3. R.Y. Zhu, Nucl. Instr. and Meth. A413 (1998) 297. 4. A.N.Annenkov et al., CMS NOTE 1997/055. 5. M.Nikl et al., J.Appl.Phys.82 (1997) 5758. 6. R.Y. Zhu, IEEE Trans. Nucl. Sci. NS-44 (1997) 468. 7. Z.Y. Wei et al., Nucl. Instr. and Meth. A297 (1990) 163. 8. P. Lecoq et al., Nucl. Instr. and Meth. A365 (1995) 291. 9. M. Kobayashi et al., Nucl. Instr. and Meth. A399 (1997) 261. 10. M. Kobayashi et al., Nucl. Instr. and Meth. A404 (1998) 149. 11. S.Baccaro et al., Phys. Stat. Sol. A164 (1997) R9. 12. E. Auffray et al., Nucl. Instr. and Meth. A402 (1998) 75. 13. Q. Deng et al., Nucl. Instr. and Meth. A438 (1999) 415. 14. X.D. Qu et al., A469 (2001) 193. 15. X.D. Q u et al., A480 (2002) 470. 16. Z.W. Yin et al., Proc. SCINT99, Ed. V. Mikhailin, (1999) 206. 17. R.Y. Zhu et al., Nucl. Instr. and Meth. A376 (1996) 319. 18. G. Bakhshiva and A. Morozov, Sov. J. Opt. Techno1 44 (1977) 9. 19. T Hu et al., in these proceedings. 20. L.Y. Zhang et al., in these proceedings. 21. R.Y. Zhu et al., Nucl. Instr. and Meth. A302 (1991) 69. 22. R.Y. Zhu et al., IEEE Trans. Nucl. Sci. NS-45 (1998) 686. 23. D.A. Ma et al., Nucl. Instr. and Meth. A356 (1995) 309.
94-38,
PERFORMANCE OF PWO CRYSTAL DETECTORS FOR A HIGH RESOLUTION HYBRID ELECTROMAGNETIC CALORIMETER AT JEFFERSON LAB
A. GASPARIAN Department of Physics, NCA&T State University, Greensboro, NC 27411, USA E-mail:
[email protected] (On behalf of the PrimEx Collaboration)
The PrimEx collaboration at Jefferson Lab is planning to perform a precision measurement of the neutral pion lifetime via the Primakoff effect. This will be a state-of-the-art experimental determination of the lifetime with a precision of less than 1.5%. Such a measurement requires an electromagnetic calorimeter with high resolution and high efficiency for detecting the photons from pion decay. A new electromagnetic hybrid calorimeter is under construction at Jefferson Lab consisting of 1200 lead tungstate ( P b W 0 4 ) crystal detectors and 600 lead glass Cerenkov modules. Recent beam tests were performed with few GeV electrons on the P b W 0 4 crystals obtained from two different manufacturers (Bogoroditsk, Russia and Shanghai, China). Results from energy and position resolution studies, and the dependence of detector response on radiation rate are presented.
1. Introduction
The PrimEx Collaboration at Jefferson Lab (JLAB) is preparing t o perform a high precision (1.4%) measurement of the neutral pion lifetime using the small angle coherent photoproduction of neutral pions in the Coulomb field of a nucleus, ie., the Primakoff effect'. This measurement will provide a fundamental test of the predictions of the axial anomaly in quantum chromodynamics. Photons from the Hall B photon tagging facility at JLAB will be used to produce neutral pions in the Coulomb field of a nucleus. At the incident photon energies of this experiment ( E y = 4.6 - 5.7 GeV), the Primakoff cross section peaks at extremely small angles ( O p e a k N 0.02'). In order to identify and extract the Primakoff amplitude, the experimental setup must have sufficient angular resolution for detecting forward produced pions. The pions will be identified by detecting the decay photons ( T O -+ yy) in the multi-channel electromagnetic hybrid calorimeter (HYCAL). Therefore, the angular resolution of the detected pions will depend strongly on both the position and energy measurement ac-
208
209
curacies of the calorimeter. In addition, the kinematical constraints imposed by the knowledge of the initial photon energy provided by the tagging system results in an improvement of the angular resolution by about 30%l. Currently, we are constructing the HYCAL calorimeter (116 x 116 cm2 area) consisting of two types of shower detectors: 600 lead glass Cerenkov modules located on the periphery of the calorimeter, and 1200 lead tungstate scintillating crystals in the central region with a hole (4 x 4 cm2) in the middle for passage of the incident photon beam. In the past decade, PbW04 has became a popular inorganic scintillator material for precision compact electromagnetic calorimetry in high and medium energy physics experiments. The performance characteristics of the PbW04 crystals are well known mostly for high energies ( > l o GeV)2 and at energies below one GeV3. In this report, we are presenting results with few GeV electrons for the energy and position resolutions, as well as the dependence of the detector response on radiation rate. These measurements were done with crystals obtained from two different manufacturers: Bogoroditsk (BTCP), Russia and Shanghai (SIC), China. 2. Experimental Setup
In order to check the performance of the crystals and to select the manufacturer, we have done beam tests with a prototype detector. A 6 x 6 PbW04 crystal array (single crystal dimensions: 2.05 x 2.05 x 18.0 cm3) was assembled in a light-tight aluminum box maintained at a stable temperature of T = 5°C. A front-view of the prototype calorimeter is shown in Figure 1. The upper 3 x 6 section of the array was assembled from crystals made by BTCP while the bottom section consisted of the ones made by SIC. The scintillation light from the electromagnetic shower in the crystals was detected with Hamamatsu R4125HA photomultiplier tubes (PMT) coupled at the back end with optical grease. Each crystal was wrapped with lOOpm millipore paper which served both as a light reflector and as an optical isolator between the blocks. The anode signal from each PMT was digitized by means of a 14-bit charge-sensitive ADC (LeCroy 1881M, integration width=200 ns). The light yield of the crystal is highly temperature dependent (- 2%/"C). In order t o keep the detector array at a very stable temperature, the crystal assembly was surrounded by thick copper plates with circulating coolants. Temperature stability at the level of AT = fO.l"C was achieved during the entire period of data collection. Secondary electrons ( E , 4 GeV) pair-produced by tagged photons in a thin radiator was incident on the crystal array. Signal from the PrimEx/Hall B pair-spectrometer system was used as the trigger for the data acquisition. For finer definition of the impact coordinates of the electrons on the crystal array, a pair of X - Y array of scintillating fibers with a fiber-width of 0.2 cm was used.
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Figure 1. The prototype lead tungstate detector.
3. Energy Resolution The energy calibration of the calorimeter was performed with 4 GeV electrons irradiating the centers of each crystal module. To measure the energy resolution, the centers of both the SIC and BTCP crystal arrays were irradiated and sufficient statistics was obtained. We found a slightly better energy resolution for the SIC crystals compared to those from BTCP. We attribute this to the relatively higher (- 20%) light yield of the SIC crystals. For the final energy and position resolution, the central part of the prototype detector was irradiated with 2 and 4 GeV electrons. The reconstructed energy distribution for the 4 GeV electrons is shown in Figure 2 for three different calibrated ADC sums: the central module; the inner section comprising 3 x 3 array; and the total array of 6 x 6 crystals. The central module already contains 75% of the total energy deposition. An excellent energy resolution of ( T E / E= 1.3% has been achieved by using a Gaussian fit of the line-shape obtained from the 6 x 6 array. After subtraction of the beam energy spread due to the finite size of the scintillating fibers, as well as multiple scattering effects in vacuum windows and in air, a level of 1.2% energy resolution was reached for 4 GeV electrons.
21 1
S225
6x6
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us 2 0 0 1 175 1
1x1 a,/E=4% 3x3 aE/E= 1.6% 6x6 aE/E= 1.3% 3x3
150 1
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+
75 1 50 L
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Figure 2. Energy response of a PbW04 crystal array to 4.25 GeV electrons. Left peak: single crystal; center peak: 3 x 3 array; right peak: 6 x 6 array.
4. Position Resolution
The impact coordinates of the electrons incident on the crystal array were determined from the energy deposition of the electromagnetic shower in several neighboring counters. In the case of the PbW04 crystals, the transverse size of the shower is about two times smaller than that in lead glass. As a result, the position resolution in the PbW04 detector with an optimal cell size should be about twice smaller than that of lead glass detectors. To maximize the position resolution, we have optimized the crystals' transverse dimensions, and have selected it to be 2.05 x 2.05 cm2. This size is comparable to the Molihre radius (2.2 cm) of the crystal material. The distribution of the reconstructed coordinates for 4 GeV electrons hitting a crystal cell boundary is shown in Figure 3. The linear dependence of the reconstructed coordinates obtained from a logarithmically weighted average of the cell signals uersus the impact positions determined by the fiber scintillator detectors is shown in Figure 4. As is well known, there is a rather strong
212 c m,
E
5 50
-1.483
40
30 : 20
Reproduced Position (mm) Figure 3. Distribution of reconstructed positions at the boundary between two lead tungstate crystal detectors.
correlation between the position resolution (oz)and the point at which the incoming electrons (or photons) hit the detector face. The bottom plot of the figure shows this dependence for the PbW04 crystals. The (T, is smaller (1.28 mm) near the edge of the cell and increases to 2.1 mm at the cell center. These tests showed no measurable difference in the coordinate resolution for the two types of crystals produced by SIC and BTCP. 5 . Detector Response versus Radiation Dose Rate
It is well known that all types of crystal scintillators are sensitive to integrated radiation dosage. In case of PbW04, one of the more important characteristics is the change in crystal response due to radiation dose rate. For crystals that were developed a decade ago, it was observed experimentally that even for a small dose rate ( 5 1 Rad/hour), the gain changes were at the few per cent level. It was understood that this effect is not a result of the change of scintillation mechanism of the material, but the loss of light output due only to absorption by radiation-induced color centers4. A dramatic improvement
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'3 30 20 3, 10 N' 0 -10 -20 3
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bx
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1
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Figure 4. Reconstructed wersus actual position (top) and position resolution (bottom) across the face of PbW04 crystal array.
of this effect has been achieved in recent years by both commercial producers of the crystals. We have done experimental studies of this effect for crystals produced in the past two years by SIC and BTCP. For these tests, several crystal centers were irradiated with 4 GeV electrons at different rates by changing the incident photon beam intensity and the radiator thickness. The duration of each irradiation was kept to about 30 minutes. The information from all channels of the 6 x 6 array prototype was recorded continuously during the irradiation process. Preliminary data of the normalized pulse-heights versus the relative beam rate for three typical crystals from each of the manufacturers is plotted in Figure 5. It was observed that above the dose rate equivalent to 4 GeV electrons at 50 kHz, the SIC and BTCP crystals show opposite behavior in detector response. This behavior could be caused by three different effects: (1) change of scintillation mechanism in the crystals; (2) change in the light transmission in the crystals; and (3) change in PMT gain due t o rate variations. Currently, N
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we are in the process of measuring performance of the PMT's at similar rates which will allow us to extract this contribution from the experimental data.
-----
SIC Shanghai BTCP Bogoroditsk
7 Figure 5. Relative pulse-height (preliminary) versus rate for SIC and BTCP PbW04 crystals. The location of the arrow indicates the dosage equivalent for 4 GeV electrons at 5 kHz obtained from GEANT simulations.
Acknowledgments This project is supported by the National Science Foundation under a Major Research Instrumentation (MRI) grant (PHY-0079840). JxeIerences 1. PrimEx Conceptual Design Report, 2000 (http://www.jlab.org/primex/). 2. Compact Muon Solenoid Technical Proposal, CERN/LHCC 94-38, LHCC/Pl (1994). 3. K. Mengel et al. IEEE Trans. Nucl. Sci. 45, 681-685 (1998). 4. R.Y. Zhu, et al. IEEE Trans. Nucl. Sci. 45, 686-691 (1998).
THE PHOTON BALL AT COSY
R.NOVOTNY, W.DORING AND M.HOEK II. Physics Institute, University Giessen, Heinrich- Buff-Ring 16 0-35392 Giessen, Germany E-mail: r.novotny4expZ.physik.uni-giessen.de
M.BUSCHER, V.HEJNY, H.R.KOCH, H.MACHNER, H.SEYFARTH AND HSTROHER Nuclear Physics Institute, Research Center Julich, D-52425 Julich, Germany
J.BACELAR AND H.LOHNER Kernfysich Versneller Instituut, Groningen, The Netherlands
A.WRONSKA Institute of Physics, Cmcow, Poland A compact photon detector with nearly 4a-coverage in solid angle has been proposed t o be implemented into the magnetic spectrometer ANKE at COSY, Julich. Based on the physics program and the experimental requirements the instrumental concept will be presented. As part of the R&D program, the response functions of PbW04 to photons and charged particles have been measured at different accelerator facilities up to energies of a few GeV and are compared to fast scintillator materials such as CeF3 and BaF2. The applicability of fine-mesh photomultiplier tubes (Hamamatsu R5505) has been tested successfully for the read-out of first prototype detectors.
1. Physics Motivation One of the internal target experiments at the cooler synchrotron COSY at the FZ Julich, Germany, is the magnetic spectrometer ANKE (Apparatus to study Nucleonic and Kaon Ejecticles), which consists of three C-shaped dipoles. They are designed to guide the beam to the target, serve as a spectrometer magnet and inflect the beam back to the original orbit. Equipped with a complex set of tracking chambers, Cherenkov detectors and plastic scintillators, charged reaction products of both signs can be detected and identified by their momentum, energy-loss and time-of-flight. The spectrometer covers a large solid angle in the forward hemisphere'.
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Strangeness production in elementary reactions at medium energies has been the primary physics motivation of ANKE,which requires the detection of meson production in nucleon-nucleon and nucleon-nucleus collisions. However, many of the exit channels are accompanied or even dominated by the production of neutral mesons as well, which can only be reconstructed via a missing mass analysis, if the measured kinematical parameters are over-determined. Therefore, a dedicated nearly 4.rr photon detector is intended to be implemented into the ANKE environment to identify directly neutral mesons via their dominant decay channels into photons and to provide even for multi meson events a complete set of physical variables. 2. The Detector Concept 2.1. Technical Constraints
A nearly complete coverage of the solid angle around the target is mandatory for the clean detection of multiple photon events. Due to the fixed geometry of the magnetic spectrometer, the vacuum system and the installation of various target devices the available space is limited to a spherical volume of 75cm in diameter. During operation the spectrometer dipoles are ramped synchronously with the COSY magnets up to a magnetic field strength of 1.6T causing strayfields up to 0.2T pointing in various directions. Therefore, the new detector to measure directly photons up to an energy of 2GeV has to accomplish the following constraints: 0
0
0
0
0
0
large acceptance for detection of multi-photon events. the invariant mass analysis requires good energy resolution (2 12x0) and high granularity. excellent timing and high count-rate capability require as well a fast scintillator as a fast photosensor operating in magnetic environment. the compact design can be accomplished only with a fast and dense scintillator material. flexible geometry to integrate different target systems and to enable fast installation. on-line rejection of charged particles via a separate veto detector system.
2 . 2 . The Detector Design
The generally limited space as well as the fixed beamline components allow the installation of a spherical detector ball of 5 75cm diameter, covering the azimuthal angle range between 25°*.The CRISTAL system, which has been developed in parallel to the construction setting-up, provides a dynamic workflow execution in a highly distributed environment at each level of the production: Each operator at his “working place” has to follow the instructions and the workflow provided by CRISTAL.
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Each operation done during the assembly of one part has to be validated. For the composite part, the exact position of each component is stored. A query facility allows for navigating the construction database at every stage of the construction and during the operation of the experiment and for retrieving the critical parameters of the crystals and capsules needed for the calibration of the detector. 5. Current production and assembly status The pre-production of the crystals started in September 1998 until December 2000, when 6000 crystals had been produced. The good quality of the preproduction crystals allowed starting the mass production of the barrel crystal in Bogoroditsk techno-chemical plant in Russia, in year 20009. In parallel to the crystal production, the two regional centres progressively set-up the module construction facility. The CERN regional centre is on production since spring 2001 and Rome since beginning of 2002. After a “warming up” period, which has allowed to test and validate all the assembly procedure and tooling in both regional centres, the following number of parts of the detector have been received, characterised and assembled using the assembly and quality check procedures described in section 4:
Element Crystals APDs Capsules Sub-units Sub-modules Modules
Number of elements 8700 30000 4000 3500 350 8
The 4 modules (see two of them in Fig. 4) for the first super-module are now ready and its assembly is currently under-work. After the full validation of the first super-module and its components, their mass production will be launched and the routine super-module assembly will start beginning of 2003 at an interval of 1 super-module per month. 6. Conclusion
The complexity of the CMS electromagnetic calorimeter and the huge amount of its components require a sophisticated and efficient organisation in terms of
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Figure 4. 2 modules (SMO/Ml & SMO/M4) of the first super-module.
management and quality control. Each production centre and particularly the two centres responsible for the module assembly have succeeded in setting-up such a good organisation that should allow building a performing detector in time.
Acknowledgments The author wants to thank all the members of the CMS-ECAL group and particularly her colleagues of the production centres.
References 1. ECAL Technical Design report, CERN/LHCC97-33, CMS TDR4 (Decl5, 1994). 2. R. Rusack, paper presented in these proceedings. 3. E. Auffray et al., Proceedings of the 1998 IEEE Nuclear Science Symposium Conference in Toronto, Canada, Vol. 1, p. 508-13 (Nov. 1998). E. Auffray et al, Nucl. Instr. and Meth., A 456, 325-341 (2001). 4. S.Baccaro et al., Nucl. Instr. and Meth., A 459 278-284 (2001). 1.Dafinei et al., Proceedings of the SCINT99 conference i n Moscow, Russia (August 16-20, 1999). 5. E. Auffray et al., CMS Note 1998-038. 6. F. Cavallari, paper presented in these proceedings. 7. N. Baker et al., Computer Physics Communication, Vol. 110, No 1-3, pp170-176, (1998). 8. A. Bazan et al., ZEEE n u n s on Nuclear Sci., Vol. 46, No 3, pp392-400, (1999). 9. E. Auffray et al., Proceedings of the SCINT2001 conference in Chamonix, fiance, (September 16-21, 2001), to be published in NIM.
Medical Applications Covener: C. Woody
C. Woody
Covener’s Report
t W. W. Moses
Synergies Between Electromagnetic Calorimetry and P E T
*C. L. Melcher
LSO - from Discovery to Commercial Development
P. Lecoq
New Scintillating Crystals for PET Scanners
J. Collot
A Simulation Framework for Positron Emission Tomography Based on GEANT4
+The perspective talk *Written contribution not received
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MEDICAL APPLICATIONS
CRAIG WOODY Physics Department, Brookhaven National Lab, Upton, N Y 11973, USA E-mail:
[email protected] (Convener’s Report)
There are a number of areas where the techniques used in calorimetry for high energy and nuclear physics are similar to those used in medical applications. Perhaps first and foremost of these involves the use of scintillating crystals and photodetectors to detect gamma rays in medical imaging and nuclear medicine. While these gamma rays may be considered low energy from the perspective of high energy calorimetry, the types of materials and the techniques used for measuring them are very similar in both cases. In addition, the need for large solid angle coverage for tomographic imaging using highly pixilated detectors is also common to both applications. More recently, there have also been many similarities in the areas of developing fast front end electronics, data acquisition, Monte Carlo techniques and image reconstruction. W. Moses gave an excellent overview on the methods and techniques used in medical imaging, particularly in Positron Emission Tomography (PET),including the use of scintillating crystals, such as BGO and LSO, and various types of readout devices, such as position sensitive photomultiplier tubes and avalanche photodiodes. These systems typically use crystals which have dimensions on the order of a few mm2 cross section by 1-2 cm in length. Human scanners used for imaging the brain have apertures with dimensions on the order of 30 - 40 cm in radius, and can contain more than 100,000 readout channels. With its fast front end electronics and high rate data acquisition systems, a P E T scanner can be seen as miniaturized but equally complex calorimeter system. C. Melcher from CTI, Inc., which is one of the world’s largest producers of P E T systems, described the development of LSO crystals for use in medical imaging. This was a particularly interesting and relevant description of what is required to produce a new crystal scintillator for use in tomography, since the same process applies for developing new crystals for calorimetry. The process begins with a detailed understanding of the basic scintillation properties of
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the material, followed by thorough study of the parameters and conditions needed for growing the crystals. In the case of LSO, this required a significant investment of time, money and resources to set up a large production facility at CTI in Knoxville, which is now successfully producing crystals for PET scanners that are sold commercially. The message from this was that the same process invariably applies to the development of any new crystal, as has occurred for BGO, BaFz, CsI, CeF3, PbW04 and others which have been used in calorimetry. P. LeCoq described the current R&D efforts by CERN and the Crystal Clear Collaboration to develop new crystal scintillators for medical imaging. This study is presently focused on the development of LuAP (LuA103), which is a new bright scintillator based on lutetium that has a density of 8.3 g/cm3 and a decay time of 17 ns. A considerable amount of effort has gone into developing LuAP by CERN in cooperation with the Bogoroditsk chemical plant in Russia, which is now producing more than 100 tons of lead tungstate for the CMS experiment. There have now been many samples of LuAP produced which show excellent light output properties, and the results look encouraging for developing this new scintillator for use in medical imaging. Several other new scintillators were also described, including those based on hafnium and barium, as well as new possibilities for increasing the light output of PbW04 that would greatly improve its resolution at low energies. This latter possibility would be very attractive given the enormous effort that has gone into developing PbW04 for high energy physics applications, and could provide a very low cost material for medical imaging. J. Collot described a Monte Carlo program based on GEANT for simulating PET scanners. While there are other simulation programs available for this purpose, the use of the GEANT program is an excellent example of the use of a tool that was developed for simulating high energy detectors being used for medical applications. This required tuning various GEANT parameters for an accurate description of the physics processes at lower energies (down to a few hundred keV) and testing the results with experimental data. The program was used to help design a microPET scanner based on liquid xenon. In summary, there are many areas where the techniques used in calorimetry for high energy and nuclear physics are common to those used in a variety of medical applications. Several examples of this were given in this session which included the development of new scintillating crystals and the use of standard simulation programs to design detectors. It is hoped and expected that these developments of mutual benefit to both fields will continue in the future.
SYNERGIES BETWEEN ELECTROMAGNETIC CALORIMETRY AND PET*
W. W. MOSES Lawrence Berkeley National Laboratory Mailstop 55-121, 1 Cyclotron Road Berkeley, C A 94709, USA E-mail: wwmoses0lbl.gov
The instrumentation used for the nuclear medical imaging technique of Positron Emission Tomography (PET) shares many features with the instrumentation used for electromagnetic calorimetry. Both fields can certainly benefit from technical advances in many common areas, and this paper discusses both the commonalties and the differences between the instrumentation needs for the two fields. The overall aim is to identify where synergistic development opportunities exist. While such opportunities exist in inorganic scintillators, photodetectors, amplification and readout electronics, and high-speed computing, it is important to recognize that while the requirements of the two fields are similar, they are not identical, and so it is unlikely that advances specific to one field can be transferred without modification to the other.
1. Introduction
There are many similarities between the instrumentation for electromagnetic calorimetry and PET. Incident gamma rays are detected (and their energy and arrival time measured) with inorganic scintillators coupled to photodetectors. Thousands of these channels are read out in parallel using custom analog integrated circuits. However, each field has its own unique requirements, which often force different optimizations to be made. This paper explores the similarities and differences between the fields. It assumes that the reader is familiar with high energy physics and electromagnetic calorimetry, but relatively unfamiliar with PET.
* This work was supported in part by the U S . Department of Energy under contract No. DE-AC03-76SF00098, and in part by Public Health Service Grants Nos Pol-HL25840 and R01-CA67911.
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2. The PET World Picture
PET is a nuclear medical imaging technique whereby the patient is injected with positron-labeled r a d i o p h a r m a ~ e u t i c a l ~This ~ ~ ~ drug ~ ~ ~ ~localizes ~. within the patient according to its physiologic properties and the radioisotope decays, emitting a positron. The positron annihilates with an electron (from the patient’s tissue) to form back-to-back 511 keV annihilation photons. As shown in Figure 1, a planar ring of 511 keV photon detectors surround the patient - if two photons are detected simultaneously (within 10 ns) then the radioisotope is assumed to lie somewhere along the line joining the two detector elements. The mathematical technique of computed tomography6, shown in Figure 2, is used to reconstruct the two-dimensional activity distribution within the plane defined by that detector ring - images from multiple detector rings are used to create a three-dimensional, volumetric image of the radiopharmaceutical distribution. PET’S strength is that it images the physiological properties of the pharmaceutical and so provides physiologic information, whereas many other medical imaging techniques provide mainly anatomical information7. For example, x-ray techniques image electron density and MRI (magnetic resonance imaging) mainly images water density. Therefore PET is predominantly used for diseases that are metabolically based (such as cancer or neurological disease). Despite the many similarities between PET and electromagnetic calorimetry, there are significant differences. One of the main constraints in PET is the low energy of the photons that must be measured with high accuracy - 511 keV is many orders of magnitude lower than the energies commonly measured with calorimeters, implying greater signal-to-noise challenges in PET. This also implies that there are no electromagnetic showers involved in PET - the only relevant interaction processes are photoelectric absorption and Compton scatter, and Compton scatter is the dominant process (at 511 keV, the photoelectric fraction is 45% in BGO scintillator and 0.02% for tissue). The high Compton fraction and relatively short interaction length (10 cm) in tissue also imply that in only a small percentage ( ~ ~done ~ at the generator level or QCD jet-jet background have obtained estimates for the rate, rj,t, at which a jet would be misidentified as a photon, and due to limited computational power, to estimate the QCD jet-jet background, the rates were simply multiplied together (factor r;,t). The problem is that the correlations within an event are not taken into account. Also the simulation was done with simplified geometry, so non-Gaussian tails in the resolution have not been adequately simulated. A special goal of this study is to simulate for the first time a large enough sample of QCD jet background to directly estimate the di-photon misidentification and compare it with contributions from other types of backgrounds. The isolation tools are important ones to isolate the signal process from
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the background one. The aim of this note is to use the isolation algorithms, which are based on information from the PbW04 electromagnetic calorimeter and the tracker, to select isolated photons from Higgs decay, while rejecting the huge jet background below the level of irreducible one. 2. Different types of backgrounds
The search for H+ yy signal at LHC has treat three types of backgrounds: 0
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Promp di-photon production from the quark annihilation and gluon fusion diagrams, which provides an intrinsic or ‘irreducible’ background (see Figure 1). Prompt di-photon production from significant higher-order diagrams - primarily bremsstrahlung from the outgoing quark line. The background from QCD jets, where an electromagnetic energy deposit results from the decay of neutral hadrons (especially isolated xos) in a jet and from 1 jet 1 prompt photon.
-+-
q
Y
Figure 1. Diagrams of irreducible background: (left) quark annihilation, (right) gluon fusion.
Table 1 shows the cross sections of different types of backgrounds. The threshold of the transverse momentum of the parton in the hard interaction process, P k T d ,which was used for generation4. 3. Simulation tools and Monte Carlo data samples
For the Higgs background study we used the following data samples:
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Table 1. cross sections of different types of backgrounds. Background process
Pkrd(GeV)
Cross section (pb)
QCD jets 1 prompt photon Brem and 1 jet Gluon fusion Quark annihilation
35 25 25 25
8x107 8x104 27 45
+
Signal: -
50K H - + yy events at mH=llO GeV
Background: - 1 million of preselected QCD jet events -
+
500K of preselected y jets events 50K of quark annihilation events 50K of gluon fusion events
All events were generated with PYTHIA 6.1524 at f i = 1 4 TeV. The CTEQ 4L parton density structure functions were used in generation. The simulation of tracking in the detector was done using CMSIM version 121 (CMSIM is a full detector simulation program based on GEANT3 p a ~ k a g e ) The ~ . simulated events were digitized using the reconstruction and analysis program ORCA‘. The digitization was done at a luminosity of 2x 1033/cm2/s. Due to the huge QCD jet cross section (0 N lo8 - lo9 pb) a strong preselection at the generator level is needed to simulate a sufficient number of background events in a reasonable time. The QCD cross section strongly depends on the transverse momentum of the parton in the hard interaction process, Therefore a proper choice of this parameter is needed to generate QCD jet events. We have chosen PkTd to be equal to 35 GeV. Further generator level preselection was performed as follows: we looked for events with at least one pair of any of the particles, y, T O , e, Q, Q’, p , w , which could deposit a significant part of their energy in electromagnetic calorimeter. The transverse energies of these two particles should be greater than 37.5 GeV and 22.5 GeV (note that proposed offline CMS cuts are 40 GeV and 25 GeV, respectively’), and invariant mass of these two particles should be in the range 80-160 GeV, which is the range where we are going to search for the Higgs in two photon decay mode. The obtained rejection factor at generator level is -3000, what means that 3000 events should be generated to produce one event to be passed through full detector simulation. Therefore one million of simulated and re-
PkTd.
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constructed QCD events corresponds to 3 x lo9 generated events. A check was done that we do not lose the events, which could fake a Higgs signal, due to the above preselection. A much looser preselection was used to simulate y jets event sample: we looked for events with at least one particle of any of the particles, y,no,e, 77, p, w , which has a transverse energy greater than 37.5 GeV.
+
4,
4 . Isolation 4 . 1 . Isolation based on electromagnetic calorimeter
Energy deposits from electromagnetic showers in the electromagnetic calorimeter are constructed into basic clusters using the Island clustering algorithm7. These basic clusters are in turn clustered into ‘super-clusters’ to recover the energy radiated from photon conversions, which fall outside the seed shower cluster7. The reconstructed supercluster is associated with electron or photon candidate. The isolation criteria is based on the sum of transverse energies of basic clusters in some cone R ( R = , / m ) around electron or photon candidates. The basic clusters, which belong to electron (photon) candidate supercluster, do not count. The algorithm contains two parameters: 0
the size of the cone R around electron(photon) candidate, where the transverse energies of basic clusters are summed. The transvere energy sum threshold, Epresh. If the sum of transverse energies is below this threshold, the photon candidate is considered as isolated, otherwise - non-isolated.
The detailed results are presented in elsewhere’. There is no strong dependence of jet rejection factor on the cone size R and the slightly better rejection factor is obtained for the cone sizes R = 0.30 - 0.35. 4.2. Isolation based on the tracker
The isolation criteria is based on the number of charged tracks, with PT greater than some PT threshold, p p T e s h ,calculated in some cone R ( R = , / m ) around photon candidate. The algorithm contains three parameters:
0
the size of the cone R around photon candidate, where the number of charged tracks is calculated. the PT threshold, p p r e s h . Only the charged tracks with p~ greater than p p T e s hare accepted for isolation.
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the ‘number of track’ threshold, Nthresh. If the number of charged tracks with PT greater than choosen ppresh, calculated in cone R, is greater than Nthresh, the photon candidate is considered as nonisolated, otherwise - isolated.
The detailed results are presented in elsewhereg. The jet rejection factor is very sensetive t o the ‘number of track’ threshold, Nthresh. By going from N t h r e S h = 0 to N t h r e S h = 1, one can increase the Higgs signal efficiency by 6-lo%, while the jet rejection factor drops by a factor of 2. Therefore we decided to fix parameter Nthresh to be equal to zero. The pFresh threshold was choosen to be 1.5 GeV.
-
5. Results
Before study the photon isolation, the 12 GeV Level 1 double isolated electron trigger was applied both for the signal and background data samples. The transverse energies of the two photon candidate should be greater than 40 GeV and 25 GeV, respectively, and invariant mass should be in the range 80 160 GeV. The fiducial volume in rapidity was restricted to 1771 < 2.5 for both photon candidates. The cross section of different backgrounds are shown in the second column of Table 2 after the above cuts were applied. One can see that the QCD jet cross section is 25 times higher than the cross section of irreducible background.
Table 2. Background cross sections, do/dmrr, in fbb/GeV. Background process
All cuts before isolation cuts
Track isolation
ECAL isolation
QCD jets 1 prompt photon Brem and 1 jet Gluon fusion Quark annihilation
2500 1200 42.3 49.7
100.0 190 35.7 40.9
30.2 112.4 33.5 39.1
+
Figure 2 shows the invariant mass distribution of different backgrounds. As expected the behaviour is smooth and decreases with increasing of the invariant mass. The last two columns of Table 2 shows the effect of isolation. One can see that the isolation is a very effective tool to reduce the huge QCD background. 15% of the total After isolation was applied the QCD background is only
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7
I
Gluon fusion
16 12
700 420
8
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0 20
7
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0
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,
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80 600 480
l&
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Bremsstrahlung and 1 jet + 1 prompt photon
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Figure 2. Invariant mass distribution of different backgrounds.
one. The overall Higgs efficiency is 33.5% after all cuts, including isolation cuts, were applied.
6. Acknowledgements We would like to thank J. Pino for the help in writing the analysis program and C. Seez for useful discussions.
References 1. C. Seez and J. Virdee, Detection of a n intermediate mass Higgs boson at L H C via its two photon decay mode, CMS TN/92-56 (1992) 2. CMS Collaboration, " T h e Electromagnetic Calorimeter Project - Technical Design Report", CERN/LHCC 97-33 (1997)
3. V. Tisserand, T h e Higgs to two photon decay in the A T L A S Detector, ATLAS Internal Note, PHYS-NO-90 (1996). 4. http://www.thep.lu.se/torbjorn/Pythia.html 5 . http://cmsdoc.cern.ch/cmsim/cmsim.html 6. http://cmsdoc.cern.ch/orca 7. E. Meschi et al., "Electron Reconstruction in the CMS Electromagnetic Calorimeter, CMS Note 2001/034 (2001) 8. V. Litvin, H. Newman, S. Shevchenko, Isolation studies f o r electrons and photons based o n ECAL, CMS IN 2002/023 (2002) 9. V. Litvin, H. Newman, S. Shevchenko, N. Wisniewski, Isolation studies f o r photons f r o m Higgs decay based o n the 'Tracker, CMS IN 2002/034, (2002)
COMPARISONS OF ELECTRON AND MUON SIGNALS IN THE ATLAS LIQUID ARGON CALORIMETERS WITH GEANT4 SIMULATIONS
D. BENCHEKROUN Universite' Hassan 11, Casablanca-Maarif, Morocco
G. KARPETIAN, R. MAZINI Universite' de Montre'al, Montre'al, Que'bec, Canada
A. KIRYUNIN', D. SALIHAGIC, P. STRIZENECt Max Planck Institut fur Physik, Werner Heisenberg Institut, Munich, Germany
J. KISH Institute of Experimental Physics, Kosice, Slovakia
K. KORDAS~,G. PARROUR Labomtoire de 1 'Acce'le'rateurLine'aire, Orsay, France
M.LELTCHOUK, S. NEGRONI, W. SELIGMAN Neuis Laboratories, Columbia University, Irvington, New York, USA
P. LOCH University of Arizona, Tucson, Arizona, USA
A. SOUKHAREV Budker Institute of Nuclear Physics, Novosibirsk, Russia
Signals from electrons and muons taken at testbeams with different modules of the ATLAS Liquid Argon Calorimeter have been compared to corresponding simulations using the GEANT4 toolkit. These simulations have also been compared in some detail with GEANT3 based predictions. Results for signal linearity, energy resolution, and shower shapes all generally indicate a good agreement between experiment and the two simulation packages, typically at the level of a few percent.
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332 1. Introduction
The ATLAS Liquid Argon GEANT4 Comparison working group has been set up to evaluate the GEANT4 toolkit' for physics simulation. This includes comparisons of relevant calorimeter performance parameters like the average response, energy resolution and shower shapes, to testbeam data and GEANT32 simulations. Results from these comparisons for electron and muon signals in various calorimeter modules are summarized in this note. First comparisons of hadron signals in ATLAS liquid argon calorimeters can also be found elsewhere in these proceedings3. This note starts out with a brief description of the relevant ATLAS liquid argon calorimeters used for the comparison, followed by a discussion of the testbeam setups and their description in the simulation. Results for muons are presented in section 4, and results for electrons can be found in section 5. 2. The ATLAS Liquid Argon Calorimeters The ATLAS detector at the future Large Hadron Collider (LHC) features a liquid argon calorimeter system housed in three cryostats, one barrel and two endcaps4. The ElectroMagnetic Barrel (EMB) calorimeter is a liquid argon/lead device featuring accordion shaped absorbers. It is about 24 radiation lengths ( X O )deep, and covers the pseudorapidity range 1771 < 1.475. The most important performance characteristics of the EMB is excellent linearity and energy resolution with stochastic terms significantly below 10% and constant terms of the order of 0.3%, all well within the requirements for physics reconstruction in ATLAS. More details on the calorimeter have been presented5 at this conference. Each of the endcap cryostats contains an Electromagnetic EndCap (EMEC), a Hadronic EndCap (HEC) calorimeter, and one electromagnetic and two hadronic Forward Calorimeter (FCal) modules. The EMEC is an accordion type liquid argon/lead calorimeter, while the HEC features a classical parallel plate liquid argon/copper structure6. The HEC is about 103 X O deep for electrons, and about 10 absorption lengths (A) for hadrons. The electromagnetic and hadronic endcap calorimeters cover 1.3 < 1171 < 3.2, approximately, while the FCal closes the gap to the beam line (3.1 < Iql < 4.9). The electromagnetic Forward Calorimeter is a liquid argon/copper device featuring tubular electrodes with thin (250 pm) liquid argon gaps for charge collection. It is about 28 Xo deep. The hadronic modules have the same * On leave of absence from Institute for High Energy Physics, Protvino, Russia t On leave of absence from Institute of Experimental Physics, Kosice, Slovakia Now at University of Toronto, Toronto, Ontario, Canada
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electrode structure, with slightly larger gaps (350 - 500 pm) and tungsten as absorber7. The around 10000 electrodes in each FCal module are oriented parallel to the beam at LHC, and arranged in a hexagonal pattern, which introduces interesting response features for this particular calorimeter. 3. Testbeam Setups in the Simulation
Test beam experiments conducted with production modules for the EMB and HEC, and special engineering prototypes for the FCal, have been described in the GEANT3 framework and using GEANT4 toolkit. To allow detailed comparisons not only to experimental signals, but also between GEANT3 and GEANT4, detailed and identical descriptions of the testbeam module and the environment are needed. 3.1. Geometry Description
Emphasis was put not only on a precise description of the calorimeter modules, but also relevant elements of the testbeam environment, like beam counters and other detectors used for trigger and particle selection, and upstream inactive materials. Figure 1 shows a part of the EMB testbeam module setup in the GEANT4 description.
lead absorber readout board
Figure 1. Th e ATLAS Electromagnetic Barrel Calorimeter in GEANT4. Th e setup includes the cryostat walls, the pre-sampler, cables and other components of the readout chain, all located at the inner (front) face of the module.
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The EMB modules used in the testbeam are actual half-barrel production modules (27r/16 azimuthal segments). The accordion structure, as seen in Figure 1, is described in GEANT4 using a combination of boxes, trapezoids and tube segments, similar to the description in GEANTS. An alternative description with a new volume shape containing one accordion absorber is available in GEANT4 only. Both geometry descriptions produce basically identical signals. The HEC testbeam setup consists of three production front and rear modules, each of which is a 27r/32 segment of the HEC wheel. The description in both simulations includes details of the readout cell, as well as virtual lateral and longitudinal leakage detectors around the actual modules allowing to estimate the leakage energies for the testbeam setup. For the FCal, engineering prototypes were used in testbeam experiments. These so-called Module 0’s are full depth, quarter segments of the full FCal modules, and have only been built for the electromagnetic and first hadronic module. Each of the about 2300 - 2500 electrodes is individually described in GEANTS and GEANT4. They are positioned using the hardware cabling and machining databases. 3.2. Simulation Conditions
GEANTS and GEANT4 use slightly different parameter spaces to control the tracking and production of particles. In GEANT4, all particles are tracked to zero kinetic energy, while the production of secondaries is controlled by a minimum range requirement. This can of course be translated into a minimum energy requirement in a given material. In GEANTS, both tracking and production energy thresholds are implemented. The tracking thresholds for e* and y in the various studied setups are 100 keV for EMB and HEC, and 10 keV for the FCal. The secondary production thresholds are 100 keV for e* in EMB, 1 MeV for e* and y in the HEC, and 10 keV for e* in the FCal, and 10 keV for y in the EMB and FCal. In GEANT4, only one range threshold at a time is specified for all secondary particles and all materials in a given setup. In the EMB, 30 pm is used, which corresponds to an energy threshold of 112(41) keV for e* and lS(1.1) keV for y in lead(argon). The default minimum range in the HEC is 700 pm, which corresponds to an energy threshold of about 1 MeV for e* in copper. Most of the GEANT4 FCal electron signals have been simulated with 500 p m range threshold, which corresponds to about 17(4.4) keV in copper(argon). In addition, the dependence of the electron signal on the range threshold has been studied for the HEC and FCal setup, in the range of 1 . ..2000 pm. Figure 2 shows the expected rise in the signals in both calorimeters with decreasing range cut, reflecting the increasing number of particles produced in
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the copper and reaching the liquid argon, thus contributing to the signal. The unexpected drop in signal around 20 pm can be observed in both setups, and is presently under study. 4. Muon Signals in the EMB and HEC Modules
Signals from muons have been studied in the EMB and HEC. The signal spectrum for 100 GeV/c muons in the EMB is shown in Figure 3. Major differences especially in the tails of the distributions can be observed for GEANT3 and GEANT4. In general the later can describe the shape to about 1%over the whole signal range, which indicates a good description of the signal contribution from &electron production around the muon track. GEANT3 does not reproduce the tails to better than 3.5%. The simulated signals from both GEANT3 and GEANT4 have been smeared by 41 MeV Gaussian electronic noise, as determined in the experiment. Both GEANTS and GEANT4 can describe the muon signal spectrum in the HEC quite well. A Kolmogorov-Smirnoff test yields the same likelihood for both simulated spectra to be identical to the experimental one. The dependence of the tails in the spectrum on the range cut in GEANT4 has been studied as well, clearly indicating a rise in the signal contribution from 6electrons when lowering the range cut from 4 to 0.2 mm. The lower value then gives the best description of the experimental data.
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Figure 3. The signal spectrum of 100 GeV/c muons in the ATLAS Electromagnetic Barrel calorimeter, as observed in a testbeam and simulated by GEANT3 (upper left) and GEANT4 (upper right plot). The corresponding cumulative differences between the simulated and measured distributions are shown in the lower plots.
5. Comparison of Electron Signals and Shower Parameters The electron response of the EMB, the HEC and the FCal has been studied extensively in testbeam experiments and with corresponding simulations. Relevant parameters used to estimate the quality of the Monte Carlo predictions are the energy dependence of the average signal, mostly introduced by inactive upstream material, the relative energy resolution, and the lateral and longitudinal shower spread. The electron signal in the EMB testbeam module, which is discussed in more detail in these proceedings', shows the expected linearity with energy to better than 1%. This is also well reproduced by the GEANT3 and GEANT4 simulations. The relative energy resolution of the testbeam module has a constant term well below 0.3%,and a stochastic term of about 9.2%. GEANT3 and GEANT4 simulations reproduce the stochastic term within the statistical errors, but only GEANT4 can predict the experimental constant term, again within errors. GEANT3 simulations show a significantly larger constant term of about 0.45%. An interesting observation in the EMB is that GEANT4 electromagnetic showers start later and are shorter (more compact) than the GEANT3 ones. This discrepancy increases with energy, and is measured by about 3% less signal in the first sampling ( w 4.3 X O )for 20 GeV/c electrons in GEANT4, and about 14% less for 245 GeV/c beam momentum. The signal in the second sampling (- 16 X o ) is between 1.5% and 2.5% higher in GEANT4, rising with
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energy, and about 5% lower in the third sampling (- 2 X o ) , rather independent of the energy. The GEANT4 electron signal in the HEC is systematically about 3% smaller than the GEANT3 signal, if a 700 pm range cut is used. Lowering this cut t o 20 pm reduces this difference to slightly less than 1%) see Figure 4. As can be seen in the same figure, the energy deposited in the absorber is correspondingly larger, so that the total deposited energy is again very comparable. The experimental electron energy resolution is very well reproduced by both Monte Carlos. A.
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The difference between GEANTS and GEANT4 simulated signals and experimental electron data has been studied in the FCal for various cell level
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noise cuts. In general GEANT4 can describe the signal dependence on this analysis cut within &l%, while GEANTS shows up to 4% mismatch with the experimental data, see Figure 4. For this study, experimental noise has been added event by event, and channel by channel, to both simulations. The compactness of the electromagnetic shower in the electromagnetic FCal, which has only one longitudinal compartment, can be measured by the cell signal significance spectrum, also shown in Figure 4. This quantity is given by the signal to electronic noise ratio in each cell. The spectrum clearly shows that both Monte Carlos have less often highly significant signals in one cell, indicating their shower composition is softer. 6. Conclusions and Outlook
The results available so far for GEANT4 electron and muon simulations in the ATLAS liquid argon calorimeters suggest that the available electromagnetic shower and muon energy loss models in this toolkit are mature enough to understand signals in complex detector readout geometries and environments at about the same level as is possible with GEANTS. Major remaining discrepancies like the signal density are addressed and under discussion with relevant experts from the GEANT4 collaboration.
Acknowledgments We gratefully acknowledge the help and support from the ATLAS testbeam communities, the CERN staff, and the involved funding agencies. In addition, we especially like to thank M. Maire (LAPP Annecy) and J. Apostolakis (CERN), both from the GEANT4 collaboration, for their help.
References 1. see http://geant4.veb.cern.ch/geant4/geant4.html. 2. R. Brun and F. Carminati, G E A N T Detector Description and Simulation Tool, CERN Programming Library Long Writeup W5013 (1993). 3. A. Kiryunin et al., these proceedings. 4. ATLAS Liquid Argon Coll., Liquid Argon Calorimeter Technical Design Report, CERN/LHCC/96-41 (1996); ATLAS Coll., A T L A S Calorimeter Performance Technical Design Report, CERN/LHCC/96-40 (1996); ATLAS Coll., ATLAS Detector and Physics Performance Technical Design Report, CERN/LHCC/9914/15 (1999). 5. S. Rodier et al., these proceedings. 6. M. Fincke-Keeler et al., these proceedings. 7. K.K. Joo et al., these proceedings. 8. D. Zerwas et al., these proceedings.
DATA VOLUME REDUCTION STRATEGIES IN THE CMS ELECTROMAGNETIC CALORIMETER
P. PAGANINI LLR, Ecole Polytechnique, Palaiseau, France E-mail: paganiniOin2p3.fr The electromagnetic calorimeter of CMS consists of a barrel and two endcap calorimeters containing a sum of over 80000 lead tungstate crystals. If all the crystals were to be read-out in a triggered event, the total amount of ECAL data would excess by a factor 20 the CMS data acquisition system limits allowed for ECAL. This paper presents the strategies developed by CMS in order to reduce the ECAL data volume to the required level.
1. Introduction The ECAL electromagnetic calorimeter of CMSl consists of 75848 readout channels (barrel plus endcap). The data are a set of samples, each one being coded after digitization, on 2 bytes. With the present ECAL raw data format, the event size is2:
Event size (Kbytes) = 37.75 +
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X Ncrystals
1024 where N c r y s t a l s corresponds to the number of crystals read-out for the whole ECAL in the event. In this formula, 10 samples per channel are assumed. However, preliminary studies3 showed that 7 samples are already enough to achieve a reasonable energy resolution and bunch-crossing identification. Using N c r y s t a l s = 75848, one gets an event size of 1.8 Mbytes. This value exceeds the total event size of 1Mbytes assumed in the DAQ design. Moreover, considering the 100 kHz level 1 trigger rate, a total bandwidth of 1440 Gbits/s would be needed to transfer these 1.8 Mbytes which is higher than the allowed value for the full CMS event builder: 500 Gbits/s. So, only 100 Kbytes per event are allocated to the ECAL data. To match this constraint, only 2656 crystals must be selected: 3.5% of the whole calorimeter. Two complementary approaches are usually considered to reach that reduction. The first one, called ”Zero suppression” is based on the rejection of informations on a channel by channel basis: only channels with energy above a certain threshold are kept. This approach is described in section 3.1. The
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second approach, called ” Regional selective readout” defines regions of interest (event by event) of the calorimeter where all channels are read-out. In the other regions, the data are either removed or a severe ”zero suppression” may be applied. The details are given in section 3.2. The next section of this paper is dedicated to the simulation of the ECAL data used for this study and their reconstruction. 2. Simulation and reconstruction of ECAL data
The CMS ECAL calorimeter consists of lead-tungstate crystals. The electromagnetic shower in this volume is simulated by a software based on GEANT 3 (in a near future GEANT 4 will be used) producing crystal hits characterized by their energy and time. The next steps of the simulation (and reconstruction) are performed by ORCA4 (Object Oriented Reconstruction for CMS Analysis) software. The front-end electronic response results from the convolution of the Avalanche Photo Diode and the multislope amplifiers responses. In the simulation, the front-end response is factorized by an electronic signal shape. Quantization noise (coming from the multislope amplifiers and ADC) are taken into account in ORCA but have been neglected in the present study. The last stage corresponds to a 40 MHz sampling of the signal shape ’. The electronic noise is taken into account by adding to each sample a typical dispersion of 40 MeV in the barrel and 150 MeV in the endcaps. Correlations among the samples have been neglected in this paper. To simulate the pile-up contribution, several events per bunch crossing are superimposed. High luminosity cm-2s ) corresponds to about 20 minimum bias events. The crystal hits resulting from these events are mixed together and their signal shape are superimposed. The resulting signal shape is then sampled. The black curve of figure 1 shows the samples energy dispersion (in GeV) as function of the crystal pseudorapidity (the RMS being used as an estimator). The transition between the barrel and the endcap (at 7 = 1.48) is clearly seen. One sees that pile-up contributes mainly in the endcap at large pseudorapidity. The crystal energy measurement is directly related t o the amplitude of the signal. The amplitude measurement has to take into account the presence of electronic noise, pile-up events and possibility of time jitter fluctuations. However, since data volume reduction will be done on-line, the algorithm must be fast enough. The method used here is based on a linear filter: the signal amplitude corresponds to a weighted sum over the samples, the weights being determined by filter theory or x2 minimization and depend on signal shape,
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a40 MHz is the LHC beam crossing frequency.
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Eta Figure 1. RMS of the samples energy distribution (in black) and RMS of signal amplitude distribution in GeV (light-grey: using basic filter, mid-grey: using optimized filter for pileup) as function of the pseudorapidity at LHC high luminosity. The value of the electronic noise used in the barrel is here 50 MeV and 150 MeV in the endcaps.
electronic noise and pile-up properties. When a filter optimized for electronic noise3 is used b , the RMS of the signal amplitude is given by the light-gray curve of figure 1, which follows closely the black one. To minimize pile-up effects, we have taken into account the correlations among samples introduced by pile-up (given by the autocorrelation of the signal shape itself3). An improvement of the RMS of the signal amplitude is shown by the mid-grey curve of figure 1. It is negligible in the barrel but can reach a few hundred MeV in the endcap. 3. Ecal data volume reduction
As already mentioned, our goal is to select only 3.5% of calorimeter channels without degrading physics performances. In CMS, we have studied 2 level of data reduction: the so-called ”zero suppression” and the ”regional selective readout”. that case, the weights depend only on the electronic noise dispersion and the signal pulse shape
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3.1. Zero Suppression
With the ”zero suppression” approach, the selection criterion is quite simple: crystals are kept if their energy is larger than a threshold. On figure 2, the fraction of kept crystals (both in barrel and endcap) is shown as function of the threshold. The light-grey curve is obtained using filter optimized for electronic noise only3, and the black one is obtained when optimal weights are used to reconstruct the signal amplitude. The second method is more efficient (see figure 2): to keep less than 3 . 5 % of channels at high luminosity, the threshold has to be set to 110 MeV in the barrel (2.20electronic noise), and to 470 MeV in the endcap (Q.10electronic n o i s e ) .
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But, applying a threshold could introduce several biases in physics quantities. For example, non-linearity effects are present in electromagnetic shower energy reconstruction as shown on figure 3 . This figure shows that for unconverted photons, the ratio between the reconstructed photon energy (obtained by a simple 5 x 5 crystals energy summation) and its initial simulated energy (called Kine on figure 3) is non linear when the energy rises. Applying a 30electronic noise threshold can introduce up to 1% non-linearity effect for photons energy between 40 MeV and 200 MeV.
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3.2. Regional Selective Readout
The readout is based on trigger tower geometry. Two thresholds are considered. Towers are classified in the following way: when the transverse energy is greater than the high threshold, towers are tagged as center towers. The towers surrounding a center tower are neighbour towers whatever their energy is. Neighbour window size can be 3 x 3 or 5 x 5 towers; when the energy of a tower is between the high and low thresholds, the tower is classified as single tower. The other towers, called suppressed tower, not yet classified, are candidate for suppression. Two schemes have been studied in CMS. In the first one2, the neighbour window size is 3 x 3 towers, and the suppressed towers are not read-out at all. Moreover, a minimal zero suppression is applied everywhere: only reconstructed positive energies are kept (negative energy can occur because of noise fluctuation). Different threshold values have been tested as shown on figure 4. The best compromise is obtained when the high threshold is set to 2 GeV, and the low one to 0.6 GeV. With these parameters, the average event size is 95 K byt es . In the second scheme5, the two thresholds are higher: 5 and 2.5 GeV and
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the neighbour window is wider: 5 x 5. Here a strong zero suppression greater than 3.50electronic noise is applied but only in towers called suppressed. The average event size also fulfills the 100 Kbytes constraint: 95 Kbytes. Both schemes are not expected to introduce bias in shower energy reconstruction since regions where showers occurs remain untouched. 4. Conclusion
CMS electromagnetic calorimeter being a very fine granularity detector, its data volume at LHC high luminosity has to be reduced to an acceptable level. With the actual specification of ECAL raw data, only 3.5% of the calorimeter channels should be selected without loss of physics performances. The solution proposed in CMS is a combination of ”zero suppression” and regional selective readout based on trigger tower. The energy thresholds used in the selection have to be low enough so that no significant effect on physics performances is observed. References 1. ECAL TDR CERN/LHCC 97-33 (1997). 2. N. Almeida and J. Varela CMS-IN 2002/009 (2002). 3. P. Busson and P. Paganini CMS-IN 2002/006 (2002). 4. D. Stickland CMS-IN 1999/035 (1999). 5. S. Rutherford CMS-IN 2002/027 (2002).
PERFORMANCE OF CDF CALORIMETER SIMULATION FOR TEVATRON RUN I1
C . A. CURRAT Lawrence Berkeley National Laboratory, 1 Cyclotron road, Berkeley C A 94720, USA E-mail: CA CurratOlbl.gov (For the CDF collaboration)
The upgraded CDF I1 detector has collected first data during the initial operation of the Tevatron accelerator in Run 11. The simulation of the CDF electromagnetic and hadronic central and upgraded plug (forward) calorimeter is based on the Gflash calorimeter parameterization package used within the GEANT based detector simulation of the Run I1 CDF detector. We present the results of tuning the central and plug calorimeter response to testbeam data.
1. Introduction
The CDF I1 detector at the Tevatron is presently taking data after having undergone major upgrades to keep up with the new operating conditions at increased luminosity and center of mass energy1. A fast simulation of the calorimeters response is a valuable and implicitly recommended tool at a hadron collider, if one wants to gain control on the systematic errors on any high-pT related physics topic while accomodating the computing time limiting factor.
CDF calorimetry for run 11 The CDF I1 calorimeter^^^^^^ - covering the region 1171 < 3.6 - are of sampling 1.1.
type with separate electromagnetic and hadronic measurements as shown on Figure 1. In both sections the active elements are scintillator tiles read out by wavelength shifting fibers embedded in the scintillator. The calorimeters are segmented in q and 4 coordinates in order to have a projective tower geometry pointing back to the nominal interaction point. It has to be mentioned that the plug calorimeters have replaced the old gas calorimeters5 used during the first generation detector (referred to as CDF I).
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Figure 1. Elevation view of one half of the C D F I1 detector with depth and sampling characteristics of the various calorimeter compartments.
1.2. The Gflash package Gflash is a fast calorimeter simulation using parameterized showers that is
interfaced with the standard GEANT-based' simulation of the detector. The program was developed by the H1 collaboration7 and is used as standard mass production Monte Carlo. Electromagnetic and hadronic showers are initiated when an incident particle undergoes an inelastic interaction inside the calorimeters. New GEANT pseudo-particle and track types are defined for the showers. Gflash uses a mixture-level GEANTgeometry for the calorimeters, i.e. the showers develop in a medium with effective density, 2, A, X O etc. It handles the energy loss of real particles inside the mixture geometry. For the electromagnetic longitudinal profiles, a standard gamma distribution is used:
where x = P z , z being the shower depth in units of X O . The average and width of CY and parameters have a typical logarithmic energy dependence. The correlation between a and P is properly taken into account when a shower
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is generated:
with matrix C describing the correlation between (Y and B determined out of GEANTresults. The terms q1 and q2 are normal-distributed random numbers around the mean values pa and pp. The lateral profiles are described by the following expression:
where & is a free parameter that is a function of the shower energy and depth. The average profile and fluctuations of individual showers are described as (approximately log-normal) functions of the energy and shower depth. Distinction is made between the core and the increasingly slower growth of the radial extent of the shower with increasing energy. The parameterization of the hadronic longitudinal profiles is a superposition of up to 3 gamma functions H , F, L to correctly reproduce the 7ro energy dependence:a
Here the (Y and O, parameters for all the gamma distributions are allowed to fluctuate and their correlations are properly taken into account. Furthermore, to get the no fluctuations right, showers are divided into 3 classes, each with a given probability. The sampling fluctuations are reproduced by depositing a Poissondistributed number of spots per longitudinal integration interval according t o the radial probability function equation 3. Their energy and hence their number are given by the energy resolution that has to be reached. These energy spots are similar to GEANT“hits” or “visible” energy depositions. In a detailed GEANTcalorimeter geometry only the energy deposited in sensitive layers, as scintillators, are recorded as hits. For mixture-level GEANT calorimeter geometries, as is the case in Gflash, one needs to simulate sampling fluctuations and to explicitely convert the deposited energy Edep into “visible” energy Evisin the active medium
aNamely, H for the purely hadronic component of the shower, F for the no fraction originating from the first inelastic interaction, and L for the no fraction from later inelastic interactions occuring in the shower development.
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where riz denotes the sampling fraction for minimum ionizing particles (MIP), and are the relative sampling fractions for electrons and hadrons, and respectively. The sum is over the electromagnetic (IC = e) and the purely hadronic ( k = had) components, with relative fraction Ck. The azimuthally symmetric spatial distribution function is given by fk(3= &fk(.z) . f k ( r ) . Further details on the implementation of Gflash can be found in the original paper7. In the following it is shown that by tuning the same shower parameterization in Gflash it is possible tQreproduce the physical response of the different sub-detectors forming the CDF I1 calorimetry.
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~ O T tuning
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The tuning of Gflash is split according t o the two sets of parameters that control on the one hand the fraction of visible energy produced in the active medium and on the other hand the energy and depth dependent spatial distribution of the various components of the shower model. All along the tuning procedure, the consistency between data and simulation is assessed with a standard x2 estimator. The tuning of hadron showers proceeds as follows: (1) The first step consists in reproducing the position and width of the MIP peak. A few parameters at a time are involved (riz,ah for each specific volume) as the simulation is still handled by GEANTat this stage. The width of the peaks is controlled by adjusting the amount of intrinsic and sampling fluctuations in the active medium. (2) A sample of 7r+ with an incident energy of 57 GeV is used next to set the energy scale for the peak of full energy deposition (involving and ck).
(3) The energy dependence of the fk = fk(E)parameters defining the fractions of deposited energy is tuned to accomodate the data at all energies. This step is basically iterative once a partial deconvolution of Ansatz equation 5 set “pivots” typically being two points with a large energy gap. (4) The tuning of the lateral profile is performed almost independently of the tuning of the longitudinal energy dependence. 2. Tuning Gflash with testbeam data
The Gflash package is tuned using testbeam data8 including electrons and pions with energies in the range 8 < E < 230 GeV.
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Focus will be made on the tuning of hadronic showers, as being the most involved part of the description. The tuning of the electromagnetic showers, although obviously valuable, presents less difficulty.
2.1. The MIP peak The MIP peak is measured in the electromagnetic compartment with pions. Besides of the position and width of the peak, the ratio of the peak content to the total number of measured pion showers provides an additional handle on the tuning, as it can be directly inferred from the geometry of the detector (see absorbtion/interaction lengths in Figure 1). Figure 2 shows the comparison between testbeam data and Gflash simulation for 57 GeV pions in the CEM calorimeter. The same level of agreement is reached in the plug calorimeter. 2.2. Setting the energy scale The hadronic energy scale in the tuning procedure is set by the response of 57 GeV pions both in the central and plug calorimeters. A set of reference plots shown on Figure 4 is used as a reference for adjusting the parameters steering the longitudinal development of the hadronic showers in the combined calorimeter compartments. Plots (a)-(d) respectively show the distribution of the measured total energy (electromagnetic+hadronic) for pions that are minimum ionizing in the PEM, the measured total energy for all the pions, the hadronic fraction of the deposited energy as measured in the PHA and the electromagnetic fraction of the deposited energy as measured in the PEM. The x2 estimator confirms that data and simulation are in fair agreement for each distribution. The same level of agreement is reached for hadronic showers in the central calorimeter. The purely electromagnetic showers are simultaneously well reproduced as illustrated on Figure 3. Plotted is the energy over momentum ratio for 11 GeV electrons. 2.3. Adjusting the energy dependence
Once the MIP distribution and the hadron energy scale are set, the other datasets can be reproduced by tuning the logarithmic dependence in energy of the shower components. Given the significant difference between the central and plug hadronic calorimeters construction, in particular when comparing their sampling structure (see Figure 1), two distinct parameterizations of the energy dependence for the fractions of deposited energy are kept ( c h , c f , ce in Equation 4).
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On Figure 5 (top) the mean value ( E / p ) of the ratio of the measured total energy over the momentum of the incident particle in the central hadronic calorimeter is plotted versus momentum. Since the scintillator-based plug calorimeter is not compensating, the response is non-linear with the pion energy. The bottom plot shows the corresponding width a ( E / p ) / ( E / p )of the distributions. Both the peak position and the energy resolution are quite well reproduced by the current tuning of Gflash over the momentum range 8 < E < 230 GeV. The same level of agreement is reached for electromagnetic showers over the same range of momenta. Error bars are displayed on both plots although mostly covered by the marker size. The main contribution comes from the uncertainty on the determination of the beam line parameters.
352 2.4. Lateral profile
For the tuning of the lateral profile, the data consist of tracks obtained from minimum bias events and measured in the central part of the CDF I1 detector. The available energy range spans from 0.5 GeV to 2.5 GeV. At higher energies, tuning follow-ups are performed with the increased amount of data becoming available. The tuning of the lateral profile can mostly be done independently of the longitudinal one. The approach is typically iterative. Figure 6 shows the comparison between the minimum bias data and the Gflash simulation. The histogram of the simulation is normalized to the data to avoid a longitudinal dependency.
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3. Remarks and conclusions The typical gain in CPU time using the Gflash parameterization with respect to the standard GEANTsimulation to generate hadronic showers is up to a factor 100 as shown on Figure 7. This work allowed the integration of a fast shower parameterization based on the Gflash package in the CDF I1 simulation framework. The calorimeters response is reproduced in an unified description over the close to 47r coverage of the detector.
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Acknowledgments The main author would like to thank the Swiss National Science Fundation (SNSF) for its support.
References 1. “The CDF I1 Detector Technical Design Report”, FERMILAB-Pub-96/390-E (1996). 2. L. Balka et al., “The CDF central electromagnetic Calorimeter”, Nucl. Instrum. and Methods A267,272 (1988). 3. S. Bertolucci et al., “The CDF central and endwall hadron calorimeter”, Nucl. Instrum. and Methods A267,301 (1988). 4. Ryutaro Oishi on behalf of the CDF Plug Upgrade Group, “New CDF end-plug calorimeter”, Nucl. Instrum. and Methods A453, 227 (2000). 5. S. Cihangir et al., “The CDF forward/backward hadron calorimeter”, Nucl. Instrum. and Methods A267,249 (1988). 6. R. Brun and F. Carminati, “GEANT Detector Description and Simulation Tool”, CERN Programming Library Long Writeup W5013 (1993). 7. G. Grindhammer, M. Rudowicz, and S. Peters, “The Fast Simulation of Electromagnetic and Hadronic Showers”, Nucl. Instrum. and Methods A290,469 (1990). 8. G. Apollinari et al., “Test beam results from the CDF plug upgrade calorimeter”, Nucl. Instrum. and Methods A409,547 (1998).
SIMULATION OF HADRONIC SHOWERS IN THE ATLAS LIQUID ARGON CALORIMETERS
A.E. KIRYUNIN', D. SALIHAGIC~, P. S T R ~ Z E N E C ~ Max-Planck-Institut fur Physik, Werner-Heisenberg-Institut, Fohringer Ring 6, 80805 Munchen, Germany
J. KISH Institute of Experimental Physics of the Slovak Academy of Sciences Watsonova 47, 04353 Kosice, Slovakia
P. LOCH University of Arizona, Tucson, Arizona 85721, USA
R. MAZINI University of Montreal, Montreal, Qc, H3C 3J7, Canada
Results of Geant4 based simulations of the response of the ATLAS hadronic endcap calorimeter t o charged pions are presented. T h e first results of hadronic simulations with Geant4 for the ATLAS forward calorimeter are shown as well. Predictions of Geant4 and Geant3 on energy response and resolution for charged pions are compared. Where it is possible, the comparison with experimental results of beam tests is done.
1. Introduction
The ATLAS Collaboration is building a multi-purpose detector for the future experiment at the Large Hadron Collider at CERN. The software is very important for the whole experiment's success. To assure its reliable maintenance over the long lifetime of about 20 years, the ATLAS Collaboration has decided to move from Fortran-based to object-oriented software. In this transformation it has started to use the Geant4 package' for the simulation of particle passage through matter. * On leave of absence from Institute for High Energy Physics, Protvino, Russia
t On leave of absence from University of Montenegro, Podgorica, Yugoslavia
* On leave of absence from Institute of Experimental Physics, Kosice, Slovakia
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Geant4 is a freely distributed simulation toolkit, based on software engineering techniques and object-oriented technology. The package was developed in 1990’s by a world-wide collaboration, and since 1999 (after first production releases) it is maintained by the international Geant4 Collaboration. The implementation of the ATLAS detector in the Geant4 framework is going on. Part of this process is the validation of the physics models in Geant4, carried out for different ATLAS sub-detectors. This talk summarises the current status of the validation of Geant4 hadronic physics, done so far for the two liquid argon (LAr) calorimeters appropriate for the corresponding studies, namely the forward calorimeter (FCal) and the hadronic end-cap calorimeter (HEC). The validation is based on the comparison of Geant4 predictions with experimental results, obtained during beam tests of calorimeter modules. Comparisons to Geant3 simulations are also available. Geant32 is the simulation package, based on the “old” Fortran software. It was heavily used over last years for analysis and understanding of ATLAS test-beam data. 2. Forward Calorimeter
The forward calorimeter in ATLAS3 is a LAr sampling calorimeter consisting of three longitudinal modules. The first (electro-magnetic) one has copper as absorber, the two following hadronic modules have tungsten absorbers. The calorimeter covers the pseudorapidity region 3.1 < 1111 < 4.9. In 1998 quarter segments of the first two FCal modules have been tested in particle beams at CERN. Evaluation of the calorimeter performance requires the comparison of experimental data, obtained at beam tests, with detailed Monte Carlo simulations. Description of the FCal test-beam setup is done in Geant4 and Geant3 exactly in the same way. This guarantees that possible difference in predictions of both simulation packages is not due to the different geometries. See Reference4 for more details on the FCal simulation framework. First very preliminary results of Geant4-based simulations of the response of the two FCal calorimeter modules to charged pions are available. For these simulations version 4.0 of Geant4 was used. The range cut was set to 20 pm. In Figure 1 reconstructed energy distributions for 20 and 60 GeV pions are presented. They clearly indicate a larger signal in Geant4 than in Geant3 (about 19 % at 20 GeV and 14 % at 60 GeV). The relative signal fluctuations are smaller in Geant4 (-18 %) than in Geant3 (-26 %) for 20 GeV, a trend that is inverted at 60 GeV, with -15 % for Geant3 and -18 % for Geant4. This can be attributed to the larger tails in case of Geant4 at this energy. Computer time, necessary for simulations, is an important performance parameter of software products. Simulations of charged pions for FCal beam
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tests with Geant4 are approximately 10 % faster than with Geant3 (for the used values of simulation cuts). 3. Hadronic End-Cap Calorimeter
The ATLAS hadronic end-cap calorimeter3 is a copper LAr detector with parallel plate geometry. It has four longitudinal layers and covers the pseudorapidity region 1.5 < 1771 < 3.2. In 1998-2001 extensive beam tests of pre-production and serial modules of the HEC were carried out at CERN. Various detailed analyses of large amounts of experimental data and comparisons with predictions from Geant3 version 3.21, allowed to evaluate the performance of the hadronic end-cap calorimeter. Main results of this work are summarised in Reference5. To validate physics of Geant4, simulations of the HEC test-beam setup were carried out. As for the forward calorimeter, geometry description of the setup was done as close as possible in Geant3 and Geant4. See Reference6 for more details on the HEC simulation framework. For charged pion simulations versions 3.2 and 4.0 (with patch 1) of Geant4 were used. The range cut was set to 700 pm. This corresponds to a 1 MeV energy threshold for particle production in copper, similar to the one applied in the Geant3 simulations. The default physics list, as provided by the Geant4 Collaboration for hadron simulations, was used. Within Geant3 GCALOR as a hadronic shower code was used. The response of the HEC modules to charged pions of different energies from 6 to 200 GeV was simulated. The
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experimentally available energy range is 10-200 GeV. The Geant4 simulations are faster than Geant3, by a few per cents. One of the important characteristics of a sampling calorimeter is the amount of energy deposited in the active and passive parts. In Figure 2 the relative (with respect to the beam energy E B E A M response ) of LAr and the summed response (copper and LAr) are shown as functions of the beam energy. Certain problems are seen in the region of 20-50 GeV: instead of smooth behaviour, there are some kind of steps. This effect is present in both used versions of Geant4. 0 Geant4-4.0 A Geant4-3.2
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The problem was recognised by Geant4 experts as a mix-and-match problem in the energy deposited by energy loss of charged particles in a pion shower. As a solution it was proposed to change the value of the maximal (minimal) energy for the low (high) energy pion model from 25 to 60 GeV (from 20 to 50 GeV). In Figure 3 the summed response is shown for the tuned version of Geant4. Evident improvement of the behaviour is observed. But there are still some small deviations around 50-60 GeV. In this Figure predictions of Geant3 are shown as well, which demonstrate good smoothness of the corresponding dependence. Another important calorimeter characteristic is the energy resolution. To
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reconstruct the energy, clusters of calorimeter cells are defined. The reconstruction procedure applied to simulated data is identical to the one used for experimental data. For direct comparison the electronic noise contributions were subtracted in quadrature from the experimental resolution. In Figure 4 energy dependences of the resolution, obtained experimentally and with Geant3and Geant4-based simulations, are presented. The energy dependence of the resolution can be parameterized by the following two term formula:
with a sampling term PI and a constant term Pz. Geant4 predicts a worse energy resolution than observed experimentally, while Geant3 gives better values than the experiment. At the same time deviations of Geant4 and Geant3 predictions from the experiment are at the same level. The HEC is a non-compensating calorimeter, which means that its response to electrons is different from its response to charged pions at the same energy. In Figure 5 the ratio of reconstructed energies of electrons and pions (e/7rratio) is shown as a function of the beam energy. It can be seen that Geant4 describes the experimental dependence significantly better than Geant3. The HEC has four longitudinal layers. Studying the energy depositions in those allows t o evaluate the longitudinal development of hadronic showers. Comparison of experimental results with predictions of simulation packages shows that both Geant3 and Geant4 are in reasonably good agreement with
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the experiment. In simulated data more detailed information about longitudinal energy depositions is available. Studies show that an average position of showers along the beam direction is closer to the calorimeter front face in Geant4 than in Geant3, at least for beam energies below 80 GeV. At higher energies average positions are very close.
360 4. Conclusions
First attempts to simulate the response of ATLAS hadronic LAr calorimeters to charged pions using the Geant4 package have been successful. After some tuning to match more accurately the low and high energy pion models, rather reasonable results were obtained. For the hadronic end-cap calorimeter, Geant4 results for the energy resolution, e/x-ratio, and the longitudinal shower profiles, are in agreement with experimental observations, at the level of a few percent. With this respect they are very comparable to Geant3 predictions. Further work on the validation of the Geant4 hadronic physics using simulations for ATLAS LAr calorimeters, is foreseen in the close collaboration with the Geant4 team. 5. Acknowledgments We would like to thank Hans-Peter Wellisch, a Geant4 expert, for the collaborative work in understanding and tuning of the hadronic code.
References 1. http://geant4.web.cern.ch/geant4/ RD44 Collaboration, “GEANT4: An Object-Oriented Toolkit for Simulation in HEP”, CERN/LHCC 98-44 (1998). 2. R. Brun et al., “GEANTS”, CERN DD/EE/84-1 (1986). 3. ATLAS Collaboration, “Liquid Argon Calorimeter Technical Design Report”, CERN/LHCC/96-41 (1996). 4. R. Mazini and P. Loch, in: Proc. IX Int. Conf. on Calorimetry in High Energy Physics (Annecy 2000), Frascati Physics Series, Vol. XXI, 485-491 (2000). 5. ATLAS Liquid Argon HEC Collaboration, Nucl. Instr. and Meth. A482,94-124 (2002). 6. A.E. Kiryunin, D. SalihagiC, P. Striienec, in: Proc. IX Int. Conf. on Calorimetry in High Energy Physics (Annecy 2000), Frascati Physics Series, Vol. XXI, 459-466 (2000).
MC SIMULATION OF THE ATLAS HADRONIC CALORIMETER PERFORMANCE
M. J. VARANDA FCUL and LIP, Av. Elias Garcia, 14, 1, 1000 Lisboa, Portugal E-mail:
[email protected] [On behalf of the Tilecal/ATLAS collaboration)
Several MC Studies of the Tile Hadronic calorimeter (Tilecal) using GEANTJ and GEANT4 have been done after tunning the code with data from tests with high energy particle beams at CERN. The comparision between the two codes started with the study of the simulation of the electromagnetic interactions and results are presented. A preliminary study of the evaluation of the simulation of the hadronic interactions is also presented.
1. Introduction The ATLAS detector is composed of several subsystems. One of them is the Tile calorimeter (or Tilecal) which is the hadronic calorimeter in the central region of the detector (I 7 151.7). The Tilecal is a sampling calorimeter made of steel as absorber and scintillating tiles readout by wavelength shifting fibers as active medium. Basically, it is a periodic structure made of steel plates alternating with scintillating tiles along the beam axis (z) and in depth (R), figure 1. It is planned to detect and measure many different physics processes which require the ability t o measure a wide range of energies, from a few hundred MeV to the TeV scale. This requires a very careful construction and accurate knowledge of the calorimeter. The modules of the calorimeter are simulated in good detail1 in Geant3 (G3) and several simulations of their response to high energy particle beams have been done and compared with data from the tests of those modules. The simulation of the calorimeter in Geant42 (G4) started a few years ago and the response of the calorimeter to e.m. interactions have been compared with the predictions of Geant3. The study of the response of the calorimeter to hadrons started just during the 2001 summer.
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Figure 1. Principle of the Tile Calorimeter. On the bottom it is the test beam setup in 2001: Two barrel modules and two extended barrel modules organized in three calorimeter layers.
2. Tilecal cell intercalibration The intercalibration of the Tilecal cells is done by running a 137Cs source inside a tube filled with water which is connected to a pump that keeps the liquid in motion. The tube passes through each tile and iron plate of the calorimeter. The mean free path of the 662 MeV photons emitted by the source is of the order of a period (18 mm), i.e, the distance between tiles (figure l), which allows to see the individual tiles and steel plates. Figure 2 shows the current produced in the PMT as a function of the source position when the source runs inside the tube with a constant speed. The peaks and valleys structure shown is due to the passage of the source through alternating layers of scintillating tiles and steel plates, respectively. The test beam data is compared with Geant3 simulation which agrees with the data with a precision of few a %. 3. Response to muons
The response of the Tilecal modules to muons was largely studied in many test beam periods. Muon beams are used in tests of Tilecal modules to intercalibrate the cells of the calorimeter and to study its uniformity.
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Figure 3 shows the response of the calorimeter to 20 GeV muon beams entering the detector at q=-0.35 and 180 GeV muon beams entering at 90°, as predicted by G3 and G4. The observed differences between the two codes are of the order of 2-3% for 20 GeV muons and up to about 5% for 180 GeV muons. For 20 GeV muons, within the experimental errors, there is good agreement between Monte Carlo and data, not sensitive to the small differences between the two codes. 4. Response to electrons
The resolution for electrons is also shown in figure 4 as predicted by both codes and as measured in the test beam. In the left plot, the experimental effects include the electronic noise that was introduced with a gaussian smearing in the simulated data. The results of the non-smeared simulation are also shown. Neither optic non-uniformities nor other experimental effects are included in the simulation. The plot shows a good agreement between the predictions of G3 and G4 but both predict a stochastic term 4% better than the data. This is most probably due to the
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Figure 3. Spectra produced by 20 GeV muons entering the calorimeter at q=0.35 (left plots) and 180 GeV muons entering at 90’ (right plots).
absence of many real fluctuations in the data that were not included in the simulation and maybe a better description of the electronic noise is also needed. In the right plot, the ratio between the energy deposited by electrons in the active material and the total energy lost in the calorimeter for beams of muons hitting the calorimeter at 90’ shows a predicted G3 signal about 1% higher than the predicted by G4. Figure 5 shows the foreseen e.m. showers in the Tilecal for 100 GeV electrons at 90°, that in G3 start later and are slightly wider than in G4. The differences cannot be checked with the Tilecal because its coarse segmentation does not allow to see which code describes better the e.m. interactions in the calorimeter. 5 . Response to hadrons
The response of the Tilecal to hadrons is shown in figure 6 and is compared with simulated data using several different hadronic packages. For the hadronic showers, the Fluka-standalone code was compared with Fluka running with G4. The e/h ratio predicted by Fluka in G4 is 1.26 while the predicted by Fluka-Standalone is 1.16 for energies between 5 and 100 GeV. The test beam data predicts e/h=1.36f0.013 for energies between 10 and 300 GeV. Gheisha re-writen for Geant4 was compared with Gheisha in Geant3. The resolution to pions predicted by Gheisha in G3 is about 3-4% higher than by
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Figure 5. Geantd and Geant4 predictions for the e m shower development of 100 GeV electrons entering at 90'.
Gheisha rewriten for G4. The test beam data is in between the predictions of the two MC codes. 6 . Summary
In general there is a good agreement between the two MC codes and the data. Both codes describe well the interactions of high energy muon beams with the calorimeter. The agreement between them is better or equal to 5% depending on the beam energy. The codes predict slightly different characteristics for the e.m. showers produced by electrons entering the calorimeter at different angles. For electrons entering the calorimeter at 90' the e.m. shower predicted by G3 starts slightly
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later and is slightly wider than the predicted by G4. The segmentation of the calorimeter does not allow to check which code describes better the data. For the hadronic showers, the e/h ratio predicted by Fluka in Geant4 is 1.26 while the predicted by the Fluka-standalone code is 1.16 for energies between 5 and 100 GeV. The test beam data predicts e/h=1.36f0.01 for energies between 10 and 300 GeV. Gheisha rewriten for Geant4 was compared with Gheisha in Geant3. The stochastic term of the resolution to pions predicted by Gheisha in G3 is about 3-4% higher than the predicted by Gheisha rewriten for G4. The test beam data is in between the predictions of the two MC’s. Acknowledgments
The author would like to acknowledge the Tilecal/ATLAS collaboration and specialy to R. Leitner, A. Solodkov and A. Henriques for the useful discussions and comments t o this presentation. The participation in the conference was supported by ICCTI and FCT, Portugal. References 1. T . Davidek, New Tilecal Beam test simulation within Dice 95/Geant3 Framework,
ATL-TILECAL-2000-13. 2. A. Solodkov, Oral presentation in the Geant4 review, 2001 M. Bosman, ATLAS, Lund Physics Workshop, 2001 3. J. A. Budagov et al., The e/h ratio of the ATLAS Hadronic Tile Calorimeter, ATL-TILECAL-2001-001.
SIMULATION STUDIES OF THE JET AND MISSING TRANSVERSE ENERGY PERFORMANCE OF THE ATLAS CALORIMETERS
M. WIELERS TRIUMF, 4004 Wesbrook Mall, Vancouver, B.C., Canada, V6T2A3 E-mail: Monika. WielersOcem.ch (On behalf of the ATLAS Collaboration)
The measurement of jets and missing transverse energy reconstruction will play an important role for many physics channels at the Large Hadron Collider (LHC). The performance of the ATLAS detector for reconstructing jets and missing transverse energy has been evaluated using detailed simulations. In this paper results based on these simulations will be shown for the jet energy resolution, in addition t o some selected examples of the simulated jet and missing transverse energy physics performance. Special emphasis will be put on the experimental aspects like electronic and pile-up noise, non-compensation, and dead material, as well as their realisation in the simulation.
1. Introduction
Reconstructing jets and missing transverse energy (EFiss)will play an important role in LHC physics. Jets will be used in many different ways, for example the jet multiplicity and the ET spectrum will be measured in the context of QCD, SUSY and other models. They will be used for reconstructing resonances like W + j j , Z + bb, and t + bW decays, as well as in searches for possible SUSY or exotic particles for example in A / H -+ TT or W’ + j j decays. For some studies such as the heavy Higgs production via the Vector Boson Fusion process a central jet veto down to transverse momenta of p~ = 15 GeV and jet tagging at large rapidities 1 ~ > 1 2 is required. Large EFiss will be an important signature for new physics, for example H + Z Z + lluu. It will be as well used to reconstruct invariant masses in decays involving neutrinos such as A / H + TT or t + lub. More details on some selected physics channels will be discussed in section 5 and 6. A detailed overview can be found in1’.
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368 2. The ATLAS Calorimeter System
The ATLAS calorimeter system is based on the liquid argon technology (LAr), with the exception of the hadronic calorimeter in the barrel. A schematic
ATLAS Calorimetry (Geant)
Figure 1. Overview of the ATLAS calorimeter.
overview is shown in figure 1. The electro-magnetic calorimeter is a Pb/LAr calorimeter with accordion geometry. It covers the rapidity region 1171 < 3.2. The total thickness is around 24 radiation lengths or 1.2 interaction lengths. To correct for the energy loss in the material in front of the calorimeter a preshower detector is preceding the electro-magnetic calorimeter. The barrel hadronic calorimeter (1.11 < 1.7) is a scintillating tile calorimeter which uses iron as passive material. The end-cap is covered by a hadronic Cu/LAr sandwich calorimeter (1.5 < JqJ< 3.2) followed by the forward calorimeter (3.1 < 1771 < 4.9), which is a dense LAr calorimeter with rod-shaped electrodes in a tungsten matrix. The total thickness of the hadronic calorimeter system is M 11 interaction lengths.
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3. Simulation of Detector Response
For the performance studies presented here, events were generated using the Pythia event generator3. Subsequently, the ATLAS detector was fully simulated using GEANT34, which is to date still the “standard” simulation program in ATLAS. Studies are ongoing to fully validate GEANT4 and in time ATLAS will move to this simulation program. An important issue is to simulate correctly the effect of pile-up in the calorimeters taking into account the read-out time. At LHC on average 23
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Figure 2. Signal shape as produced in the detector (triangle), and after shaping (curve with dots). The dots represent the position of the successive bunch crossings at LHC.
minimum bias events will be present per bunch crossing at design luminosity ( L = 1034m-2s-1 ). In the calorimeters the read-out time is much longer than the bunch spacing time of 25 ns. In the LAr calorimeter system, the bipolar shaping functions have a response to a triangular signal that lasts for over 500 ns (see figure 2). They are designed so that the noise will peak at zero energy. The read-out in the tile calorimeter is much faster. The response is a unipolar shaping function which is approximated by a Gaussian distribution with a FWHM of 50 ns. Thus, to generate one signal event at design luminosity around 700 minimum bias events need to be added. Currently to generate these events in ATLAS two methods are used. In both methods the minimum bias events are read via a secondary stream. The first approach is to add pile-up in a fast way at reconstruction time to a given signal event via a direct access file which is kept in memory. This method only works for the calorimeter, and in case where correlations with other detectors need to be taken into account a much slower method is used. In this case pile-up is added in an additional simulation step for all detectors. Here the GEANT hits coming from the main bunch crossing are added for all ATLAS detectors. In addition, a third data
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stream takes care of pile-up events from very early or late bunch crossings, which are not seen by all detectors. At present the pile-up simulation is done using FORTRAN, but work is ongoing to implement a similar mechanism in our offline framework which is written in C++. 4. Jet Reconstruction
The aim in jet reconstruction is, in most cases, to extract from the energy deposits in the various calorimeters the energy of the initial parton. To do so, many factors have to be taken into account which can be subdivided into two groups: experimental and physics related factors. Among the experimental factors are dead material in front of the detector and non-sensitive regions, non-compensation, longitudinal leakage, lateral shower size, read-out granularity, non-linearities, electronic and pile-up noise, and magnetic field effects. Physics related factors are initial and final state radiation, fragmentation, the underlying event, and the model to simulate minimum bias events. In addition, effects due to the jet reconstruction algorithm need to be taken into account. There are two basic groups of jet finding algorithms. In ”cone-like” algorithms a cone is drawn around a seed, which for example might be the centre of a calorimeter cell with a local energy maximum. The different methods vary for example in the strategy to calculate the jet directions or in the treatment of dealing with overlapping nearby jets. ” Cluster” algorithms are inspired by QCD and rely on pairing of ”particles” (approximated by calorimeter towers) starting from the closest particles. All these different algorithms suffer from a bias in the energy measurement as a function of ET due to the effects discussed earlier in this section. In summary, there is no unique strategy for jet reconstruction and the best approach will depend on the physics process t o be analysed, the jet reconstruction algorithm chosen, and the luminosity condition. For example, different jet algorithms will be used in ATLAS t o study the QCD jet multiplicity at low luminosity ( L = 1033c7r-2s-1) compared t o high p~ reconstruction of W -+ j j decays at design luminosity. Using a simple cone algorithm with AR = 0.7 the jet resolution based on the detector aspects is DE/E= 5 2 % / 0 @ 3 . 0 G e V / E @ 1 . 7 %at low luminosity. At design luminosity a cone size of AR = 0.7 cannot be used due to the effects of pile-up noise. The ET r.m.s. is 4.7 (14) GeV in a cone with AR = 0.4(0.7) at design luminosity. Using a cone of AR = 0.4 the resolution is D E / E = 81%/@ @ 3.9GeV/E @ 1.7%. These numbers will improve as we develop more sophisticated methods to correct for all the different detector effects. Figure 3 shows the resolution together with the contribution of the physics related factors on the resolution for a cone algorithm of size AR = 0.4. It can be seen that the intrinsic physics contribution is smaller but still of the same
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order as the contribution of the experimental factors. The algorithmic flow of the jet reconstruction package in the offline ATLAS C++ software which is currently being developed, can be divided into three distinct parts. The first one is the detector level. The calorimeter cell signals are reconstructed and calibrated to the electro-magnetic scale. Afterwards the information of the different calorimeters can be combined to form towers or clusters. The second part is the actual jet reconstruction, which consists of jet finding, reconstruction and calibration. The jet energy calibration will be a key issue due to the variety of experimental and physics related effects. Insitu physics processes like Zo+ jet and W + j j will be used, combined with information obtained in test beam runs. After all jets in an event are found, there is a jet classification step, in which they will be labelled as b-jets, Tjets, or light quark jets. One important requirement in the jet reconstruction software is flexibility and that for example any of the steps in the whole chain can be redone if desired. 5 . Physics Examples for Jet Reconstruction 5.1. Forward Jet Tagging and L o w - p ~Jet Veto
Forward jet tagging will be an important tool to select Vector Boson Fusion (VBF) processes. The signature of these processes is characterised by accom-
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panying jets in the forward region and little hadronic activity in the central rapidity region. A tagging efficiency of x 90(80)% can be achieved at (771 < 4 with a fake rate of M 10% at low (design) luminosity (see figure 4). The effi0.9
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Figure 4. Left: average p~ of forward quarks and forward jet tagging efficiency as a function of rapidity. Th e efficiencies are given at low and design luminosity. Right: jet veto efficiencies in the central region ((171 < 2.5) for heavy Higgs production via VBF and for tf background. The efficiency is defined as the fraction of events with no additional jet with a p~ larger than the jet veto p~ threshold. Results are shown for low and design luminosity as found using either the fast simulation (ATLFAST) or the full simulation (DICE).
ciency decreases for 171 > 4 because the average p~ of the quark decreases. A jet veto in the central region helps t o reduce the background. This background mainly arises from t f events which typically have a strong hadronic activity in the central region of 171 < 2.5. The efficiency to veto jets in this region is shown in figure 4 for the heavy Higgs production process H -+ WW + Zvjj. For a 60% efficiency, the t f background can be reduced by approximately a factor of 10. 5.2. Reconstruction of Resonances
Jets will play an important role in reconstructing resonances decaying to jets. Two examples are shown in figure 5. The first example shows the jet-jet invariant mass peak from W decays at design luminosity. The typical ET of the jets, in that sample, is 120-150 GeV. The tail to lower masses is due to a bias in the jet direction when the jets overlap. The hadronic W decay will play an important role in many physics signals at the LHC, such as the search for SUSY particles or the heavy Higgs boson, the measurement of the
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top quark mass, and QCD studies. A more complex example for a resonance reconstruction is the decay H -+ hh -+ bbbb, which is shown on the right hand side of figure 5. For this analysis it is assumed that the mass of the light Higgs is known. This mass is used as mass constraint to reduce the combinatorial background and t o recalibrate the b-jet energies. 6. E F s a Reconstruction
At LHC, the reconstruction of the missing transverse energy (EFi"")will be used for invariant mass reconstruction in decays like A / H -+ TI-. Some discovery channels for new physics, for example in SUSY models, involve a large EFiss. For these channels it is important to minimise the EFiss fake rate due to instrumental effects such as non-sensitive areas. EFissis reconstructed from cell energies over the full calorimeter coverage (1771 < 5). For a good EFiss measurement an accurate calibration is vital. ATLAS envisages to have different calibrations applied to cells within clusters and those outside. On the left side of figure 6 the resolution of the two components ( p ~ s s , p ~ i of s sthe ) EFiss vector is shown at low luminosity. The p:?" can be parametrised as p:?" = 0.46 . At design luminosity the pile-up noise contributes an additional 15 GeV to the resolution. On the right side of figure 6 the effect of badly reconstructed or undetected jets on the EFiss measurement is shown. Assuming the jet from Z+jet events is undetected large EFissmight be reconstructed. However, if these jets are reconstructed by the standard jet reconstruction program the EFiss is much
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smaller. A rejection factor which is larger than 1000 is achieved for E F s s > 200 GeV.
7. Conclusions Jets and EFiss will play an important role in many physics analyses at LHC. Performance studies based on events with fully simulated detector response have shown that the calorimeters are well designed for jet and E F s s reconstruction even in the "high-noise" environment at design luminosity. Further improvements in many regions are expected over the coming years. References 1. The ATLAS Detector and Physics Performance Technical Design Report, CERN/LHCC/99-14( 1999). 2. The ATLAS Calorimeter Performance Technical Design Report, CERN/LHCC/96-40 (1996). 3. T. Sjostrand, Computer Physics Commun. 28, 227 (1983). 4. R. Brun et al., CERN/DD/EE/84-1 (1996).
JET ENERGY RECONSTRUCTION WITH THE CMS DETECTOR
SKUNOR1 University of Maryland, College Park M D 2074.2, USA E-mail:
[email protected] The CMS calorimeter is a non-compensating calorimeter and has non-linear response to jet energy. A 4 Tesla magnetic field in a tracking volume induces extra smearing of energy measurement by the calorimeter. Various algorithm to improve the measurement have been tested. A simple mapping of the calorimeter response to jets is implemented in the trigger and more sophisticated energy flow algorithm may be used at a later stage.
1. Introduction
The CMS calorimeter has been designed for precise energy measurements of photons and electrons in the psuedorapidity interval 1 ~ < 1 2.6, and moderate precision energy measurements of quarks and gluons in 1771 < 5.0 through the measurement of jets of p a r t i c l e s ' ~ ~ >The ~ . central calorimeter (-q1 < 3) consists of P b W 0 4 crystals for the electromagnetic calorimeter (ECAL) and scintillator-brass (70% Cu, 30% Zn) sampling calorimeter for the hadron calorimeter (HCAL). The forward calorimeter (3 < 171 < 5) is a quartz fiber calorimeter with iron absorber. The response of the calorimeter to photons is quite linear versus incident energy, while the response to hadrons depends strongly on incident energy4. This quite different response of the calorimeter t o photons and hadrons leads to a nonlinear response of the calorimeter to jet energy and a smearing effect in the energy resolution. Since the calorimeter response depends on the total energy of a jet (not the transverse energy), the transverse energy scale of jets showed a strong psuedorapidity dependence. In order to restore the energy scale of reconstructed jets and t o improve the resolution, we have studied various algorithms for correcting the jet energy. Simpler algorithms use only information from the calorimeter. More complicated algorithms require reconstructed charged tracks. In the following sections, we describe those algorithms and their performance.
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376 2. Initial Reconstructed Jet Energy
We use the iterative cone algorithm with a cone size R=0.5 to reconstruct jets through this Monte Calro study. The energy of reconstructed jets is calculated as a simple sum of energy in ECAL and HCAL in the jet cone, i.e.
+
Ere,, = (EC H C ) (1) EC and HC are reconstructed energy in ECAL and HCAL, respectively. The energy scale of ECAL was calibrated with electrons. The energy scale of HCAL was calibrated with charged pions ( E ~ = 3 0 G e v of ) which shower started in HCAL. Therefore, E,,,, has a right energy scale for photons, but lower for most of pions in jets because of lower response of ECAL to hadrons. 3. Jet Energy Corrections
In order to correct the jet energy, we have tested several algorithms. All algorithms are intended to remove detector effects in jet energy reconstruction and not to make correction for parton energy. In order to translate energy of jets to energy of partons, we need additional correction for fragmentation process of partons and it is beyond the scope of this study. 3.1. Simple map of Calorimeter Response
The simplest correction algorithm5 uses a form of
EcoTT(&, 71) = ~ ( E T71), x Ere,,(&, 71) (2) A calorimeter response function, a(ET,q) =< Egene > / < Ere,, > was created using a Monte Carlo QCD jet sample. Since this approach corrected the energy scale by simply multiplying by a correction factor, it did not improve the energy resolution for individual jets, but did improve trigger turn on curves’ and reconstruction of dijet masses by equalizing the jet energy scale in the whole range of r] in the detector. For example, it provided 35% improvement in the resolution of di-jet mass for Higgs (115GeV) decaying to b-quark jets6. 3.2. Use of Longitudinal Segmentation
The CMS calorimeter has mainly two longitudinal segmentation- ECAL and HCAL. In order to improve the resolution of individual jets, our first attempt was to utilize the longitudinal segmentation’. We optimized two coefficients a(ET,q) and b(Et,71) in the following formula with QCD jets sample to obtain the best energy resolution.
EcoTT = ~ ( E T , vx) EC
+ b(ET,V) x HC
(3)
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The improvement in relative resolutions before and after the correction was 4% on average in the wide range of ET and 77. For example, the resolutions before and after the correction were 14.3%and 13.6%,respectively at ET=80GeV and 77=0.2, i.e. 5% improvement in relative resolution. The improvement was not large. This lack of improvement may be attributed to the relatively thick ECAL compartment ( 1.1 interaction length) without any longitudinal segmentation. In general, a calorimeter can be divided into three longitudinal sections. The first section measures mainly showers due to photons in a jet, the second section measures a mixture of showers due to photons and hadrons, and the third section measures showers due to hadrons. By optimizing a weight for the second section one can somewhat compensate a different response of calorimeter to photons and hadrons, consequently improving jet energy resolution. The thick ECAL subsumes the second section completely. Therefore, there was not much room to improve the jet energy resolution by optimizing longitudinal calorimeter weights in the CMS calorimeter.
3.3. Use of Transverse Shower Size Contrary to the longitudinal segmentation, the CMS calorimeter has very fine transverse segmentation in ECAL (A7 x A@= .0174 x .0174). We tested to separate electromagnetic clusters (em) and hadronic clusters ( h a d ) in a jet cone using the transverse shower shape in ECAL and then apply correction coefficients to em and had, separately. A preliminary result shows that the separation of em and had clusters is not clean in terms of transverse shower size in ECAL. Therefore improvement of resolution is expected to be small8. 3.4. Correction f o r Out-of-Cone Tracks
Relatively soft tracks can be swept away from the jet cone by 4T magnetic field. For example a track with P ~ = 1 . 6GeV is deflected by the magnetic field by A@= 0.5 radian from the original direction when it reaches the calorimeter surface. Tracks with PT 5 0.8 GeV never reaches the barrel calorimeter. Fig. 1 shows a fraction of the energy of generated jets escaping from the jet cone in 4T field. One can see that on average about 15 % of the energy of the soft (- 30 GeV) jets escapes from the jet cone and there are big fluctuations of this energy. Adding the energy of the out-of-cone tracks to the calorimeter jet energy removes the fluctuations and therefore improve the jet energy resolution. Fig. 3 and Fig. 4 show the jet energy resolution and linearity as a function of the generated jet ET. The resolution is improved significantly with addition
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of out-of-cone tacks(dots vs. opensircles). Also we have tested the correction using all Monte Carlo generated tracks and actually reconstructed tracks with our current track reconstruction program and found no significant difference between two cases. The efficiency of track reconstruction is 90% with a PT cut off at 0.9GeV. This efficiency and the cut off energy are sufficient to improve the jet energy resolution.
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7 GeV/c) and imposing the relation AT = AR/c valid for particles moving at the speed of light, between the time and space distances of hit cells. With this procedure, the time offsets are determined with a precision of w 50 - 80 ps in half an hour of cosmic ray data taking. Fine corrections to the time offsets are obtained using yy events by minimizing the time residuals T - R/c between cluster times T and distances from the interaction point R. The accuracy reached is 20 ps for 100 nb-' of collected data. The time resolution is measured using the T - R/c distributions of prompt photons from radiative Bhabha and 4 decays (Fig. 2). The time resolution scales as ot N 56 p s / d m fB 133 ps. The constant term (W
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is mostly due to the finite bunch length. Since the start to the calorimeter TDC's is provided by the level-one trigger, after synchronization with the radio frequency signal, all the measured times are known up to a multiple of the radio frequency period (TRF = 2.715 ns). The T - R / c distribution of yy events, reflecting the spread in trigger time formation, shows well separated peaks (Fig. 3, left). The distance between the peaks gives an estimate of TRF.The correction to the time calibration constants is obtained dividing the measured value of TRF by the expected value. Non linearities in the distribution of T - R/c as a function of the photon impact position, which lead to a systematic error in the time scale measurement of up t o 1%, have been carefully corrected. The time scale is then checked in K L -+ T+T-T' decays by comparing the position of K L decay vertex obtained using drift chamber tracks with the one obtained using the impact positions and arrival times of photons in the calorimeter. In Fig. 3 (right), the residuals between the charged and neutral vertex positions are shown ~ t as function of the K L flight path for two different samples, with and without correcting for systematics. The slope in the distribution disappears in the former case, showing the correctness of the time scale calibration. References 1. KLOE collaboration, M. Adinolfi, et al., submitted to Nucl. Znst. Meth. A. 2. KLOE collaboration, M. Adinolfi, et al., Nucl. Znst. Meth. A482,363 (2002).
MONITORING AND CALIBRATION OF THE BELLE ELECTROMAGNETIC CALORIMETER
KENKICHI MIYABAYASHI Department of physics, N a m Women's University Kita- Uoya-Nishi-machi, N a m 630-8506, Japan E-mail: miyabaya4hepl.phys.nam-wu.ac.jp (For the Belle Electromagnetic Calorimeter Group) We report monitoring and calibration issues to have stable operation of the Belle electromagnetic calorimeter. As a result, good mass resolutions for no and 7 are obtained to be 4.8 and 12.1 MeV/c2, respectively. The degradation of light output due to the radiation damage is small, about 3% for the radiation dose of 40rad.
1. Introduction The Belle detector' is working at the interaction point of the KEKB e+ecollider2 to detect B meson decay products to study C P violating phenomena. In order to cover various topics related to B decays, high resolution electromagnetic calorimetry is indispensable to reconstruct neutral particles such as y,T O , q and so on. Also the electromagnetic calorimeter plays an important role in electron identification3. In this report, we describe monitoring and calibration issues to achieve good performance to match physics requirements. 2. Calorimeter construction
2.1. CsI(Tl) crystal calorimeter The Belle electromagnetic calorimeter consists of 8736 CsI(TZ) counters. Out of these, the barrel calorimeter has 6624, while the forward and the backward endcap calorimeters have 1152 and 960 counters, respectively. The coverage in the polar angle(@)with respect to the electron beam axis is 12" < 8 < 155' in the laboratory frame. The barrel part has 1250mm inner radius. The mechanical support structure is comprised by aluminum inner wall and fins suspended from stainless steel made reinforcing bars and outer walls. In Ref.l, the details about the calorimeter construction are described.
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Each CsI(T1) crystal is 30cm long and its cross section is 5.5cmx5.5cm at the front face where particles come in. The crystal is wrapped by 200pm white Gore-Tex film reflector, then is wrapped by a laminated sheet of 25pm thick aluminum and 25pm thick mylar. The aluminum layer works as an electric shield, while the mylar layer electrically separate the counter from the mechanical supporting structure. On the rear face(readout surface), two pieces of PIN photodiodes are glued via l m m thick lucite with an epoxy glue. Each photodiode has lcmx2cm active area. Just behind those, two preamplifiers are equipped inside a metal casing which is fixed on the crystal by screws. By a CsI(T1) counter, typically 1 MeV energy deposit yields about 5000 photoelectrons. In the operation of the first three years, there is no dead counter out of 8736 crystals. 2 . 2 . Readout electronics
The schematic diagram of the readout electronics is shown in Fig. 1. As described in the previous subsection, each photodiode signal is received by a charge sensitive preamplifier and integrated independently. These two outputs from each counter are summed at the first stage of a shaper-QT board located near the Belle detector. The summed signal is shaped with two different shaping times of 200ns and 1ps. The former goes to the calorimeter trigger system, and the latter is fed to a charge to time(QtoT) converter chip(MQT3OOA) for the energy measurement. The output of MQT3OOA is a ECL differential signal. The number of edges of pulse within the proper time window denotes the selected range and timing of the edge corresponds to the input pulse height. This is the mechanism of QtoT conversion with auto range selection. Finally, a signal is digitized by a FASTBUS TDC(LeCroy 18778). Using this scheme, a wide dynamic range corresponding t o 18bits is achieved, while incoherent and coherent noise contributions per crystal are 19OkeV and 17keV4i5,respectively. In order to reduce data size, a crystal hit which does not exceed 0.5MeV is suppressed on the TDC. In average, there are about 2000 hits in an event under this scheme. This treatment does not sacrifice energy resolution at all. 2.3. Monitoring tools for stable operation
Since a preamplifier consumes the electric power of 0.15W, in total the electromagnetic calorimeter generates a heat of a few kW inside the Belle detector structure. We have a cooling facility with water circulation and in total 312 thermistors are installed to monitor the temperature. Before installation, we tested a hygroscopicity of a CsI(T1) crystal and we found that low humidity less than 15% is necessary to avoid a damage on crystal surface. Based on
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this result, the dry air facility is installed and humidity monitoring is carried out by 104 humidity sensors(HUM1TTER). During a regular operation these environment parameters are kept to be quite stable; temperature change is less than 0.1"C and humidity is always less than 6%. Such stable conditions contribute a lot to ensure stable detector operation. Each CsI(T1) counter has a piece of LED inside the preamplifier casing. Since there are enough number of methods as described in the following section, it is used to check whether the counter is alive.
3. Calibration From the digitized signal of i-th counter(TDCi), the energy deposit(&) is obtained by the following formula;
where PEDi and ei are the pedestal and electronics gain constant of i-th counter which are obtained by the daily electronics calibration run, while Ci is determined by physics events. We obtained the initial Ci by cosmic rays before beam collision. It allowed the quick start of the calorimeter with good performance at the initial stage. After physics run started, we obtain Ci for e+e- collision data with Bhabha and e+e- -+ yy events by minimizing the x2 defined as follows.
x2=c
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where j , Esumj, Eexpj and (T are the event suffix, the total energy of j th event, the expected total energy deposit of j-th event and the estimated energy resolution. This minimization results in the matrix inversion method. As shown in Fig. 2, the matrix inversion fairly converges. In actual calibration 1.2
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procedure, Bhabha calibration is carried out at first because of higher statistics. And then fine tuning is done by efe- + yy process since it has less systematics due to the material in front. Note that we use cosmic-rays calibration constant for inner-most crystals in the endcaps, because we have too small statistics in those crystals due to the degradation of shower reconstruction efficiency caused
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by a quite thick material in front. In addition, some of them do not match back-to- back condition. Since each counter is calibrated by Bhabha and e+e- + yy processes, i.e. crystals are calibrated at the highest energy point, there can be a non-linearity of the reconstructed energy in low energy region(be1ow 1GeV). We carefully checked such effect using no signals and correct it by comparison between the data and MC no mass peak value. This correction amounts about 2% for a lOOMeV energy photon, as shown in Fig. 3.
Non-linearity correction (applied by div. for Exp. Data)
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As the resultant performance, no and q mesons reconstructed by two photons are shown in Fig. 4, where each photon is required to exceed 50MeV. The obtained mass resolutions are 4.8 and 12.1 MeV/c2 for no and q, respectively.
Figure 4. The invariant mass distributions of two photons; #(left) and q(right) regions. Here each photon is required to exceed 50MeV. The obtained mass resolutions are 4.8 and 12.1 MeV/c2 for 7r0 and q, respectively.
4. Monitoring crystal's radiation dose and light output
Since the cosmic ray runs are carried out without beam, those datasets are suitable to monitor intrinsic light output of the crystal. The dark current of photodiodes is monitored and it gives us the radiation dose of the crystals. By these measurements, we can know the light output of crystals as a function of the radiation dose as shown in Fig. 5. During three years operation the crystals in barrel and endcaps have a radiation dose of -10rad and -40rad, respectively. The light output degradation is -2% in barrel and -3% in endcaps. AS a result, our CsI(T1) calorimeter has enough radiation hardness as tested before installation" 5. Conclusion The Belle CsI(T1) calorimeter has been working quite well for three years. The energy resolution for e+e- -+ yy is 1.7%. The no and q mesons are reconstructed by their decays into two photons with the mass resolutions of 4.8MeV/c2 and 12.1MeV/c2, respectively. All the 8736 CsI(T1) counters are
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Dose (Radkrystal) Figure 5. The light output change plotted as a function of radiation dose.
alive. The light output degradation by radiation dose was found to small; about 3% even in the endcaps after three years running. We can conclude that we can enjoy much more B physics with neutral particle reconstruction. References Belle Collaboration, Nucl. Instrum. Meth. A479,117-232 (2002). KEK Report 95-7 (1995). K. Hanagaki, H. Kakuno, H. Ikeda, T. Iijima, T. Tsukamoto, hep-ex/0108044. H.Ikeda et al., “A detailed test of the CsI(T1) calorimeter for Belle with photon beams of energy between 20MeV and 5.4GeV”, Nucl. Instrum. Meth. A441,401426(2000). 5. H.Ikeda, “Development of the CsI(T1) Calorimeter for the Measurement of C P violation at KEK B-Factory” , Ph.D Thesis, Nara Women’s University, 1999. 6. K.Kazui et al., “Study of the radiation hardness of CsI(T1) crystals for the Belle detector”, Nucl. Instrum. Meth. A394 46-56(1997). 1. 2. 3. 4.
CALIBRATION AND MONITORING OF THE ZEUS URANIUM SCINTILLATOR CALORIMETER AT HERA
M. BARB1 Physics Department, McGill University, 3600 University Street, Montreal, Quebec, Canada, H 3 A ZT8 E-mail: barbiOmail.desy.de
(For the ZEUS Calorimeter Group) One of the main components of the ZEUS detector at the HERA storage ring is the Uranium Calorimeter (UCAL). It has been running successfully since ZEUS started data taking in 1992. The UCAL is a Uranium-Scintillator calorimeter with equal = 1.00 f 0.05 ), a linear energy response response for electrons and hadrons (
9 a
%
and a high energy resolution of = 18% for electrons and = for hadrons. It covers 99.7% of the solid angle and is able to handle bunch crossing rate of up to 10.4 MHz. This performance demands a very precise calibration and a constant monitoring of the detector. In this paper we present the procedure to achieve a calibration accuracy of better than 3% and to maintain it stable to better than 2% for more than10 years.
1. Introduction
The Uranium Sampling Scintillator Calorimeter1Ji3 (UCAL) is the main calorimeter of the ZEUS experiment3 at HERA, a electron-proton collider at DESY with a center of mass energy of 324 GeV2. This calorimeter type is unique in the world. The intrinsic uranium radioactivity and the high uniformity of the signal response over the entire calorimeter allow a simple, accurate and stable calibration, making this calorimeter a central component for all precision measurements of the HERA physics programme. The calorimeter provides precise energy and arrival time measurements which are used for different applications from trigger decisions to jet reconstruction. This contribution describes the methods used to calibrate and monitor the ZEUS Uranium Calorimeter.
2. ZEUS Uranium Calorimeter Architecture The main design criteria of the calorimeter were as follows:
40 1
402
(1) high energy resolution - essential for any high precise measurement; (2) high time resolution - to detect and suppress background like cosmic rays and beam gas events which are out of phase with the bunch crossing; (3) good spatial resolution - to be able to identify efficiently scattered electrons; (4) uniformity - equal signal response throughout calorimeter is essential for any precision measurement (5) stability (6) fast response - to be able to handle the 10.4 MHz of the HERA bunch crossing rate with a minimal readout deadtime.
These requirements are partially achieved by using the sampling principle which allows to tune the electromagnetic and hadronic parts of the hadronic shower to compensate. A small sample depth is used to guarantee a high resolution in electromagnetic shower measurements. Each layer is made up of 3.3 mm of stainless-steel-clad depleted-uranium and 2.6 mm of SCSN-38 scintillator, corresponds to 1.0 XO (0.04 X)I and is uniform throughout calorimeter. The thickness of the cladding of the DU is 0.2 mm. Figure 1 shows the ratio f of the electron to hadron signals as a function of the energy EK of the incident particle in the calorimeter. The UCAL has depleted-uranium (DU) as passive material. It has the advantage of producing slow neutrons by fission which helps in compensating the losses in the hadronic shower. The uranium acts also as an absorber of electromagnetic particles generated in the electromagnetic part of the hadronic shower, enhancing the compensation mechanism. As active material scintillator is used. It contains a large fraction of hydrogen atoms that produces the signal by interacting with the slow neutrons from the hadronic shower. The calorimeter is divided in three different regions, namely the forward (FCAL), the central (BCAL) and the rear (RCAL) sections, covering the polar angle ranges 2O - 40", 37O - 129' and 128' - 177". The FCAL and RCAL are subdivided in 23 modules each and the BCAL is subdivided in 32 modules. Each module consists of towers segmented longitudinally into two parts. The inner part constitutes the electromagnetic section (EMC) with a depth of 25 XO (1.1XI) throughout UCAL and the outer one constitutes the hadronic section (HAC) with a depth of 6 XI in FCAL, 3 XI in RCAL and 4 XI in BCAL. The EMCs are further segmented in 4 (2 in RCAL) sections and the HACs are subdivided in 2 (1 in RCAL) sections of 3.0 XI in FCAL (RCAL) and 2.0 XI in BCAL.
403 1.1
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Figure 1. The ratio 2. The calorimeter is fully compensating for energies above 5 GeV and approaches the electron to mip ratio at low energies.
Due to the compensation and uniformity, the calorimeter has a high = 35% The electromagnetic energy is hadronic energy resolution of
9 a* measured with a resolution of 9= %. The UCAL can also measure the
time with a resolution better than 1 ns and the position with a precision better than 1.3 cm vertically and 0.8 cm horizontally. This allows a good identification of the scattered electron in DIS process and an efficient suppression of background events out of phase with the bunch crossing. 3. Calorimeter Readout
The calorimeter readout4 is designed such as to ensure a very stable system able to handle a high bunch crossing rate with very low deadtime. The light of each EMC and HAC cells is collected by 2 wave-length shifter guides (WLS) mounted at the two sides of a tower. The light is then sent to a photomultiplier (PMT) that is connected to a front-end card where the signal is splitted 5-fold: 0
0
0
0
to two shaping-sampling with different (high and low) gains; to a current sum node, serving the Calorimeter First Level Trigger (CFLT); to a current integrator averaging the input current over 20 ms and providing the uranium calibration signal measurement; to a termination resistor.
404
The signal is sampled and stored in a 58 cells deep pipeline chip continuously clocked at the 10.4 MHz bunch crossing rate until a first level trigger occurs. Then the readout stops for 10 ps and 6 samples for each gain are transferred to a 8 cells deep buffer chip clocked at 0.6 MHz to the digital cards (DC’s). This scheme allows 5 ps for a trigger decision and leads to a deadtime of 1% for a first-level trigger rate of 1 kHz. Each DC has 4 analog-to-digital converters (ADC’s), a digital signal processor (DSP) and a memory in which the calibration constants are stored. The latter are used subsequently in the DSP’s to correct the 12-bit digitization results from the ADC’s and to reconstruct the time and energy to be used in the second-level trigger and to be sent to an event builder. The 12-bit digitization, along with the 2 gain scales, allows an effective dynamic range of 17 (15) bits in FCAL and BCAL (RCAL). The dynamical range (high gain)(low gain) per Calorimeter cell is (0-24 GeV)(O-530 GeV) in FCAL, (0-18 GeV)(O-380 GeV) in BCAL and (0-18 GeV)(O-90 GeV) in RCAL, while the noise level is dominated by the uranium activity (UNO) of x15 (x25) MeV in the EMC (HAC) sectors. 4. Calibration Method and Monitoring
The calibration5 of the calorimeter is based on its uniformity and on the natural uranium activity (2-10 MHz per calorimeter cell) that provides the absolute energy calibration. A total of 16 modules were examined in test beams at CERN2, where the construction tolerance and its implication on the uranium signal calibration was extensively investigated. An averaged non-uniformity of less than 1%were measured, the main contribution occurring in regions across the modules and towers boundaries. Cell-to-cell calibration was measured to be better than 1.5% (2%) for EMC (HAC) sections. The nominal UNO currents are chosen such that the response of each cell to mip’s scales with the number of layers in the cell. The calibration constants were transported from test beam to ZEUS and then a set of corrections are applied in order to keep the UNO current at the nominal level. The corrections are obtained from a full electronic calibration, an adjustment of the high-voltage applied to the PMT’s and a measurement of offline energy normalization factors. In the full electronic calibration, the calibration constants are adjusted for the front-end cards and the digital cards. A digital-to-analog converter (DAC) on board of each front-end card allows to set a very precise reference voltage used to measure the pedestal and gain of the pipeline and buffer chips. In addition this voltage is injected into the buffer-multiplexer and used to measure the ADC-to-VOLT constants. A very stable and known amount of charge is
405
used to calibrate the gain of the shapers. Finally, the uranium noise offset is measured. All the constants are subsequently stored in the DSP on board of each digital card, as already mentioned in the previous section. The constants are found to be stable to much better than 1%over a week. Figure 2 shows a schematic of a front-end card.
I’M
41 J 4
CIN
CLK
COllT
IWLSE
444 CLK
fi
US7
CLK R S T H * M C
CONTHOL SIGNALS
Figure 2.
A calorimeter front-end card.
In addition to the full electronic calibration, the high voltages (HV) applied to the photomultipliers are adjusted such that the response of the detector to the UNO current is kept to the nominal one within less than 1%. The uranium current measured at DESY is used for such purpose. Figure 3 shows the relative deviation of a measured UNO current to the nominal one after a HV adjustment. Figure 4 shows the stability of the UNO current measured at different time in a period of 36 days. Ultimately, the UNO current is recorded daily for use as offline normalization correction factors. Beside the above corrections, a constant monitoring ensures a good quality of the signal. The calibration stability is checked daily and the bad channels are marked and removed from the readout. Dedicated runs are used for this purpose, namely:
406
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20 15
10
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-0.02
-0.01
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0.01
0.02
0.03
Relative Deviation from Nominal UNO
Figure 3. Nominal UNO current measured in test beam for a FCAL module and the relative deviation of a UNO current measured at DESY after a HV adjustment showing an agreement to much better than 1%.
(1) Pedestal (Ped) runs; (2) Charge injection (Qinj) runs; (3) Uranium noise (UNO) runs; (4) LED runs; (5) Laser runs.
The pedestal runs are used to check the whole readout chain from the photomultipliers to the digital cards. Any channel with bad pedestal is marked and removed from the readout. The UNO and Qinj runs are used for the same purpose of checking for bad channels. The first monitors the uranium activity tracing down malfunction of photomultipliers or HV systems and the latter checks the stability of the electronic readout. Figure 5 shows the results of the measurement from these three runs. We can clearly recognize single bad channels or groups of them. They are marked and fixed whenever possible. The LED and laser runs measure the light (LED) and laser pulse3 injected in the WLS guiders and can be used as a double check for the performance of the photomultipliers, the HV system and the electronic readout. They are also used to study the photomultipliers gain stability and linearity over a wide
~
407
RMS of 0.2 X Period of 36 days UNO token after calibration 0
80
-
60 -
40 -
20
-
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Figure 4.
"
'
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~
~
"
"
~
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UNO current measured at different time showing high stability.
dynamic range. As a result of all corrections and monitoring, the calorimeter has typically 2% of the total readout channels declared as bad, the number of bad cells is usually less than 2 and the calibration is stable to 1 - 2%.
5 . Summary
The calorimeter uniformity and the compensation ensures a high hadronic energy resolution. The natural uranium activity provides the absolute energy scale and an in situ calibration is performed to correct for changes in the readout electronic. The nominal uranium noise current from the test beam measurement is re-established by adjusting the high voltage based on the measured uranium current at DESY. The latter is recorded on daily basis for use as offline normalization factor. A complete monitoring of the readout system is performed and bad channels are removed from the readout. The calibration is stable to 1 - 2%. However it is worth mention that the absolute calibration from the test beam to ZEUS is good only to 3 - 4% which is taken into account by using physics constraints6.
'
408
60 40
100
50
2000
150
20
0 Oinj x PMT number
100
50
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Oinj RMS x PMT number
400
300 200 100
2
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UNO x PMT number
100
200
UNO RMS x PMT number
2
0 50
-2 50
100
150
200
100
150
200
0
Pedestol x PMT number
Pedestol RMS x PMT number
Figure 5. Charge injection, U N O and pedestal runs used to monitor the readout channels. Those ones outside the calibration tolerance are marked as bad and removed from the readout.
Acknowledgments
I acknowledge the support of the ZEUS collaboration and, in particular, the ZEUS calorimeter group for the discussions, comments and materials used in this paper. I am thankful to Rik Yoshida for his excellent remarks and advises and to Wolfram Zeuner for his critical reading of the draft. References 1. M. Derrick et al, N I M A 3 0 9 , 77 (1991). 2. A. Andresen et al, N I M A 3 0 9 , 101 (1991).
3. The ZEUS Detector Status Report 1993, D E S Y , (1993) 4. A. Caldwell et al, ZEUS-Note, 92-022 (1992) 5. J. Crittenden, The Performance of the ZEUS Calorimeter, Proceedings of the I/
International Conference o n Calorimetry in HEP, Brookhaven National Laboratory, USA, 1994 6. M. Wing, Determination of Jet Energy Scale Using the ZEUS Detector, Submitted to the Proceedings of the X International Conference o n Calorimetry in H E P , Calthec, USA, 2002
CALIBRATION OF THE PHENIX LEAD SCINTILLATOR CALORIMETER
H. TORI1 Kyoto University, Oiwake-cho, Sakyo-ku, Kyoto, 606, Japan E-mail: htoriiObnl.gov (For the PHENIX Collaboration)
In the early summer of 2000, the PHENIX experiment for heavy-ion physics at RHIC began, and that for spin physics was started in 2001. In this experiment, the electromagnetic calorimeter (EMCal) plays an important role in detecting photons and electrons/positrons. In order to cover topics in both areas of physics, e.g., thermal photon measurements in heavy-ion physics, and prompt photon, ?yo and weak boson measurements in spin physics, the EMCal must cover a wide energy range from a few hundred MeV to 80 GeV. Spin physics also requires the energy measurement to be within 2% accuracy for measuring cross sections of prompt photons and ?yo production with 10% errors, because the cross sections have steep ) The PHENIX EMCal consists of a lead scintiltransverse momentum ( p ~ slopes. lator (PbSc) and lead glass (PbGl). In this paper, we will report the performance of the PbSc and the achievement of 2% accuracy.
1. Lead Scintillator CaIorimeter(PbSc)
The PbSc is a Shashlik-type sampling calorimeter made of alternating tiles of lead and scintillator. The basic block is a module consisting of four towers which are optically isolated and are read out individually'. The module has a 5.52 x 5.52 cm2 cross section and 37.5 cm length. The most important feature is its find segmentation, which is the 0.01 rapidity. The two photon from a r0 of p~ = 30 GeV/c will be separated. In this section, some basic performance known from beam test are will be shown.
1.1. Energy Linearity and Resolution From several beam tests at B N L 1 ~ 2 ~and 3 ~ 4 CERN5, the PbSc was found to have a nominal energy resolution of CTE/E = 2.1% @ 8 . 1 % / a from 0.5 to 80 GeV/c as shown in figures 1 and 2, where 69 represents the quadratic sum.
409
410
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-8 0
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/
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/
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3
4
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Figure 1. Energy linearity measured at BNL(1eft) and CERN(right) beam test.
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CERN 10-80GeVIc e
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it
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s::::::The ~ . use of the
46 1
W* 4 e*v, process, however, relies on the performance of the tracker since the E/p matching is the only constraint for this process. We are thus interested in using additional physics process for the ECAL calibration, especially at the beginning of data taking, when LHC runs at cm-2 s-l. This report cmP2 s-' or relatively low luminosity, such as describes an investigation on absolute calibration using the J / $ -+ e+e- and "(1s) + e+e- processes. The advantage of these processes is the high cross section and that the physics constraints are entirely within reach of the ECAL. The disadvantage is the requirement of a very low p~ cut in Level 1 trigger. In this study, we try to calculate the cross sections of these processes, and simulate the trigger rate by taking CMS detector as an example. The result of this study indicates that about 1 or 0.5 year data taking at relatively low luminosity of 1032Cm-2s-1 or 1033Cm-2s-1 respectively is required to reach a sub percent calibration precision by using electron pairs from the J / $ production. A combination of all physics processes thus may be needed to achieve required precision quickly at the beginning of data taking. 2. Production Cross Sections
PYTHIA 6.136 is used to calculate the production cross sections of Z o ,W*, J/$J and Y(1s) at LHC. Since most processes in PYTHIA are calculated at the tree Level, CDF data were used to estimate the amplitude of corrections, or the Ic factor, which includes high order corrections. 2.1. Z o
+ e+e-
The CDF data for inclusive Zo production6, followed by muon pair decay, is ~ ( p -+p 2') . B r ( Z o -+ p'p-)
This cross section at o(@
= (233
* 18) pb.
fi = 1.8 TeV, calculated from PYTHIA, is + 2') . B r ( Z o -+ p'p-) = 172 pb.
(1)
(2)
Equations 1 and 2 indicate that the correction, or the k factor, to the Z o production cross section is 1.35, which is consistent with the estimation (1.3 1.4) by the QCD tools working group7. PYTHIA gives the cross section for the Zo + e+e- calibration process at LHC (6 = 14 TeV) as ~ ( p -+ p 2') . B r ( Z o + e+e-) = 1.85 nb.
(3)
Assuming a Ic factor of 1.35, we have our best estimate of .(pp
+ 2') . B r ( Z o + e f e - ) = 2.5 nb.
(4)
462
The energy (E), transverse momentum ( p ~ )pseudo , rapidity (77) and opening angle of two electrons from Z decay ( A R = distributions for electrons from Zo decays are shown in Figure 2. The peak of the p~ distribution is at 45 GeV and the opening angle of two electrons peaks at 180". A p~ cut as large as 10 or 15 GeV for the Level 1 trigger does not degrade the statistics.
d
AK
Figure 2. E, p ~17 and , A R distributions for electrons from Z o decays at LHC.
2.2. W
m
)
11
Figure 3. E, p~ and 7) distributions of electrons from Wf decays at LHC.
-+ ev
The CDF data for inclusive W* production*, followed by decays t o an electron and a neutrino, is ~ ( p -+ p W ). BT(W -+ ev) = (2.49 f 0.12) nb.
(5)
The corresponding total cross section calculated by using PYTHIA is
a ( p p -+ W ) . BT(W + e v ) = 1.88 nb.
(6)
Equations 5 and 6 indicate that the k factor for the W production cross section is 1.33, which is similar to the case of the 2' production. PYTHIA gives the cross section for the the calibration process of W* -+ e*v at LHC (fi = 14 TeV) as a ( p p -+ W ). BT(W -+ ev) = 20 nb.
(7)
463
Assuming a k factor of 1.33, we have our best estimation as a ( p p -+ W ) . Br(W -+ ev) = 26.6 nb,
(8)
which is a factor of 11 larger than that of 2 -+ ee. The energy (E), transverse momentum ( p ~and ) pseudo rapidity (77) distributions for electrons from W* decays are shown in Figure 3. These distributions are very similar to those of electrons from the 2' decays.
2.3. J / $
+ e+e-
The CDF data for inclusive J/$ productiong, followed by muon pair decay, is ~ ( p -+ p J/$,pT > 5 GeV, 1771 < O.~ ).BT(J/$-+ p+p-) = (17.4f0.1
ti::) nb.(9)
This includes near 20% from b hadron decays, about 10% from $(2S) decays and other 70% from the direct J/$ production and xc decays. In PYTHIA, the production of J/$ consists of 4 processes, 99 -+ J/$g,
99 -+ xcog, 99 -+ xclg, and 99 -+ xc2g,
(10)
where x C o , xcl and x c 2 can decay to JIG. Taking into account the branching ratio of J/$ -+ p+p-, we have a(pF -+ J/$,pT
> 5 GeV, lql < 0.6). Br(J/$
-+ p+p-) = 3.77 nb,
(11)
which is much lower than CDF data. By using Equations 9 and 11,the k factor for the J/$ + e+e- process is estimated to be 4.62, which is much larger than that for the Zo and W* productions. The PYTHIA cross section of J/$ production at LHC is a ( p p -+ J/$) . Br( J/$ -+ e+e-) = 8.53 pb.
(12)
By using the k factor of 4.62, we have a ( p p -+ J/$) . Br( J/$ + e+e-) = 39.4 pb,
(13)
which is a factor of 16,000 larger than that of 2 -+ ee. Figure 4 shows the energy (E), transverse momentum ( p ~ )pseudo , rapidity (17) and opening angle of two electrons ( A R ) distributions for electrons from J/$ -+ e+e- process at LHC. The peak of the p~ distribution is at 1.5 GeV, and the opening angle of two electrons from the J/$ decay has a broad peak between 120" and 180". To use most of the electrons from J/$ decays the p~ cut should be as low as 1 GeV.
464
AH
Figure 4. E, p ~7 and , AR distributions for electrons from J / $ decays at LHC.
2.4. Y ( l s )
Figure 5 . E, p ~q ,and A R distribution for electrons from T(1s) decays at LHC.
+ e+e-
The CDF data of inclusive "(1s) productionlo, followed by p pair decay, is da -(pp
dY
-i T(ls),y
=0 , p < ~ 16 GeV).Br(T(ls) -i p+p-) = (753f29f72) pb(
Since the Y(ls)'s y distribution is almost flat when 1y1 a ( p p -i T(ls),IyI
< 0.4, we have
< 0 . 4 , ~lo) and low hit multiplicities (510) with solid and dashed lines. The energy resolution is obviously better for events with higher hit multiplicities. Right panel: True interaction depth vs. deviation between reconstructed and true interaction depth (Az) of the simulated events. The reconstructed vertices here are obtained using the analytic 4-hit vertexing algorithm. The size of the squares corresponds to the number of reconstructed events in the Monte Carlo simulation.
4. Monte Carlo Event Simulation
Monte Carlo Event Simulation: A Monte Carlo which takes into account the gross features of the calibration results has been developed to simulate
519 neutrino events. Fake u, events are simulated in a rectangular box shaped region 2 km on a side around the RICE array and 1 km in depth. After specifying a vertex location and the u energy, a radio signal from the shower created is simulated using GEANTlO Thermal noise is also simulated at each Ftx location. The event is reconstructed using a 4-hit vertexing algorithm after taking care of the amplifier gain and the cable loss, and smearing the signal by uncertainties in the gain ( f 6 dB) and the Ftx time ( f 2 ns). The source direction is determined by fitting a Cherenkov cone of 56" half width to the hit Ftx's. The results from 10,000 simulated Y, events with energy 10 PeV each are plotted in Figs. 3 & 4.
0
50
100
150
d0 (true-reconstructed direction)
Figure 4. Monte Carlo prediction for RICE array angular resolution in units of degrees. More than half of the simulated 10,000 events are reconstructed within 10 degrees 3f the actual event locations.
Figure 5. RICE 95% CL upper limits on the u, flux (shown with heavy lines). Also shown are different flux models used to calculate the limits. The flux models are, at l o 7 GeV from top to bottom, correspond to (i) Stecker & Salamon, (ii) Protheroe, (iii) Mannheim-A, (iv) Protheroe & Stanev, and (v) Engel, Seckel & Stanev.
5. Results
The RICE array was operating in a stable configuration during August 2000 and data from that period have been analyzedll The total experimental live time for August 2000 was 333.3 hrs, during which time the experiment detected no Y event. Based on non-observation of a Y event, 95% C.L. limits have been put on the Y, flux corresponding to various flux models13 (see Fig. 5).
520
6. Summary and Outlook RICE is signal, not background limited. It attains the vertex, angular and energy information necessary to identify a Y event. RICE demonstrates the radio technique to detect UHE v’s works. With one month of fully analyzed data, RICE has achieved the upper limits on v, flux competative with other experiments in the 100 PeV - 10 EeV energy range12 Future improvements under consideration for RICE include (i) deploying more antennas in future AMANDA/ICECUBE holes to increase the exposure, (ii) adding a hadronic shower component in the simulation, (iii) transmitting signal via optical fiber and/or in-ice waveform processing, (iv) rejecting surface background in hardware and (v) improving signal t o noise ratio using crosspolarized antennas.
Acknowledgements We thank AMANDA for logistic support. RICE was also Supported by grants from the National Science Foundation Office of Polar Programs, the University of Kansas General Research Fund, the NSF EPSCoR Program, the University of Canterbury Marsden Foundation, and the Cottrell Research Corporation.
References 1. 2. 3. 4.
5. 6. 7. 8. 9. 10. 11. 12. 13.
G. A. Askar’yan, Sov. Phys. JETP14, 441 (1962). M. A. Markov and I. M. Zheleznykh, Nucl. Inst. Meth. A248, 242 (1986). A. L. Provorov and I. M. Zheleznykh, Astropart. Phys. 4, 55 (1995). J. P. Ralston and D. W. McKay, in Arkansas Gamma Ray and Neutrino Workshop 1989, edited by G. B. Yodh, D. C. Wold, and W. R. Kropp [Nuc. Phys. B (Proc. Suppl.) 14A, 356 (1990)], reprinted in Proceedings of the Bartol Workshop on Cosmic Rays and Astrophysics at the South Pole, AIP, New York (1990). G. Richter, J. P. Ralston, and D. W. McKay, Phys. Rev. D53, 1684 (1996). D. Besson in Radio Detection of High Energy Particles 2000, AIP Conf. Proc. No. 579, AIP, Melville, NY (2001). D. Saltzberg et al., Phys. Rev. Lett. 86, 2802 (2001). P. B. Price, Astropart. Phys. 5, 43 (1996). I. Kravchenko et al., astro-ph/Oll2372, (2002). S. Razzaque et al., Phys. Rev. D65, 103002 (2002); in Radio Detection of High Energy Particles 2000, AIP Conf. Proc. No. 579, AIP, Melville, NY (2001). I. Kravchenko et al., result paper, (2002). J. Learned, in Neutrino 2002, Munich, Germany (2002). F. Stecker and M. Salamon, Space Sci. Rev. 75, 341 (1996); R. Protheroe, ASP Conf. Ser. V121, 585 (1997); K. Mannheim, Astropart. Phys. 3, 295 (1995); R. Protheroe and T. Stanev, Phys. Rev. Lett. 77,3708 (1996); R. Engel, D. Seckel and T. Stanev, Phys. Rev. D64, 093010 (2001).
RADIATION HARDNESS STUDIES OF HIGH OH- QUARTZ FIBRES FOR A HADRONIC FORWARD CALORIMETER OF THE COMPACT MUON SOLENOID EXPERIMENT AT THE LARGE HADRON COLLIDER
I. DUMANOGLU, E. ESKUT, A. KAYIS-TOPAKSU, N. KOCA, A. POLATOZ, G. ONENGUT Cukurova University, Adana, Turkey
J.P. MERLO, N. AKCHURIN~,u. AKGUN, s. AYAN, P. BRUECKEN, I. SCHMIDT, Y. ONEL University of Iowa, Iowa City, U.S.A
A. FENYVESI, K. MAKONYI, D. NOVAK Atomki, Debrecen, Hungary
M. SERIN, M. ZEYREK Middle East Techn. University, Ankara, Turkey (This paper was accepted, but not presented in the Calor.200.2)
Darkening of various types of high OH- fibres were studied by irradiating them with 500 MeV electrons. The transmission of Xe light was measured in situ in the 300-700 nm range. The induced attenuation at 450 nm is typically (1.52 f 0.15) dB/m for 100 Mrad absorbed dose. Two-parameter fits for darkening were presented. After irradiation the tensile strength remains essentially unchanged. For Polymicro quartz core fibres the tensile strength is typically (4.6 f 0.4) GPa.
1. Introduction The Large Hadron Collider(LHC) will collide protons at 14 TeV centre of mass energies. The Compact Muon Solenoid(CMS) experiment' is one of the two general purpose detectors, and is optimised for searching new phyiscs at the LHC. The Hadronic Forward(HF)2 calorimeter is a sub-detector of CMS and will cover the pseudorapidity of 3 < q < 5. The HF consists of quartz fibres Now at Texas Tech University, Lubbock, USA
521
522
embedded in an iron absorber. Particles hitting the absorber generate showers, and subsequently some of these secondary particles produce Cherenkov light in the fibres. At LHC during the high luminosity running, the HF will receive doses up to 100Mrad/year at q = 5. The radiation hardness of the fibres to various type of particles is crucial for satisfactory operation of this detector. Darkening, recovery and mechanical strength of the various types of fibres were studied by irradiating them using 500 MeV electrons which were delivered by the Linear Injector(L1L) for Large Electron Positron (LEP) collider at CERN. 2. Experimental Setup and Data Taking
LIL delivers 500 MeV electrons to LEP in supercycles of 19.2 s which consist of 16 cycles each with 1.2 s duration. The fibres were irradiated in the LIL experimental area (LEA) in parallel with LEP operation. To get an aproximately constant dose rate, only 4 cycles of supercycles were used. Each cycle delivers 120 bursts of 10 ns duration(fwhm). At 6 x lo9 e-lbwst, the mean rate is 1.5 x 10l1 e-/s and the instantaneous rate is 4.8 x 1017 e-/s. The mean dose over the fibre length for an exposure to 10l6 e- is about 40 Mrad; the corresponding dose rate is 600 rad/s. The fibres were embedded in an iron bar (40 mm high, 12 mm thick and 1 m long) which was placed on a remotely controllable table. Two fibres were placed at 4.5 mm depth from the front surface of the iron and a set of radiophotoluminescence (RPL)3 dosimeters were inserted behind them for measurement of dose during irradiation. The iron absorber was installed at a slope of 8% relative to the beam direction. Electrons will see an effective thickness of 5.5 cm of iron in front of the fibres. This configuration allows the maximum of 500 MeV electron shower to be in the iron where fibers were installed and to transfer the maximum possible dose to the fibres. Sweeping the beam horizontally within 8 cm allows us to irradiate 100 cm of the sample fibres. The optical setup uses components from Ocean Optics, Inc. A two-channel spectrometer (SD2000) triggers a Xe lamp and reads the transmitted light intensities at the different wavelengths. The Xe lamp generates a spectrum in the range of 160-1000 nm. Spectrometer is sensitive to light between 300nm to 800nm. All optical components and fibres were coupled with SMA connectors. All measurements were done in situ. The Xe light pulses were sent through a 35 m long fibre, to a Y fibre which splits the incoming light into two irradiated fibres. The transmitted light coming from two sample fibres is transmitted along two other long fibres and terminates at the slave and master channels of the spectrometer. This
523
setup allows direct comparison of two sample fibres as a function of time. The light source and spectrometer were kept at constant temparature (10f 1)OC. The experimental area where the fibres were irradiated, was at room temperature. The integration time was set to 100 ms. The beam was turned off every 2 minutes to prevent any light generation due to beam crossing. The beam was turned on as soon as the sample spectra were recorded. The fibres were exposed to a dose of about a 100 Mrad. The number of electrons, time t, and table position were recorded and monitored until the end of the irradiation.
3. Analysis and Results Table 1 shows the charecteristics and origin of the the tested fibres. Fibres were supplied mainly from two different companies. All fibres have a quartz core (9) but quartz(q) or plastic(p) cladding. able 1. Characteristics and origin of the tested fibres. Fibres were manufactured in Polymicro echnologies Inc., US (PT), and in Hesfibel, Turkey (H). SSU type preform were produced either Russia (R) or by Heraeus in Germany. F-110 is only produced by Heraeus. Diameter (pm) c/cl/b
Quartz/Origin
Core( c)/clad( cl)/buffer(b)
SSU (G)/Heraeus
Silica/F-silica/Kapton
300/330/370
SSU (R)/Russia
Silica/F-silica/Kapton
300/315/345
F-110 /Heraeus
Silica/Polymer/ Acrylate
300/330/500
F-110 /Heraeus
Silica/Polymer/ Acrylate
300/330/350
SSU (G)/Heraeus
Silica/F-silica/ Acrylate
300/315/345
SSU (G)/Heraeus
Silica/F-silica/Kapton
400/440/480
SSU (R)/Russia
Silica/F-silica/Kapton
400/420/460
FllO /Heraeus
Silica/Polymer/Acrylate
400/430/730
FllO /Heraeus
Silica/Polymer/ Acrylate
400/430/450
3.1. Direct Comparison of Two Types of Fibres The ratio of the two transmissions p y x , t ) = RQ, t ) / R j ( X ,t )
gives a direct comparison of the two fibres tested, independently of dose rate, Xe lamp fluctuation or other systematic effects. Ratios p33(A,t ) and p77(A, t ) were measured and were close to 1 as expected. Using these ratios, we estimate the systematic error of the ratio R to be f3% at 100 Mrad.
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Figure 1 shows comparison of fibres 2 and 4 (see table 1 for fibre specifications). As can be seen from the figure, while the difference is small at 450 nm it becomes larger a t 610 nm. Different quartz preforms (Heraeus for qp and Russian for qq) were used in the core of the fibres. Both fibres were manufactured by PT. After the beam stop, we continued to take data for recovery measurement. During the recovery phase, the ratio stays almost constant following some recovery adjustments.
“‘
“Q 1.3 1.2
1
Darkening
1.1
Figure 1. Ratio of normalised transmission of qq (no : 2) and qp (no : 4) fibres (300prn) drawn by Polymicro with G(qp) and R-quartz(qq). Upper curve at 450 nm, bottom curve at 610 nm. One hour of darkening correspond to 2.16 Mrad.
3.2. Darkening of Fibres At our level of precision the relative attenuation of light is negligible for the wavelengths longer than 720 nm. To remove the effects of changes in the fibre geometry due to table motion or the few percent fluctuations in lamp, the spectra were “renormalised” to the part of the spectra in the range 720-780nm. Induced attenuation of the fibre as a function of dose and wavelength is expressed as: A(X1 D)= -(10/L)los[I(X, D ) / I ( X , 0)l
(2)
525 where A(A, D ) is attenuation in dB/m at dose D and wavelength A, L is the length of fibre in meters and I ( X , D ) is transmitted light intensity at dose D and wavelength A. A(X, D ) is usually represented with the following two-parameter function:
A(A, D) = a(A)Da(’) We fit the ratio of spectra to extract the parameters a ( A ) and
(3)
p(X) :
I(A,D ) / I ( X ,0) = e ~ ~ [ - 4 . 3 4 3 L ( ~ ( X ) ( D / D , ) ~ ( ~ ) ]
(4)
For a dose unit D , = 100 Mrad, a ( A ) is attenuation in dB/m at 100 Mrad. Figure 2 shows relative transmitted spectra versus dose for PT qp fibre (no:4). The fit parameters a ( A ) and p(X) are presented in Figures 3 and 4, respectively. The systematic relative error on the ratio I ( X , D ) / I ( X ,0), estimated as f 3 % (see section 3.1), results in an absolute systematic error on the attenuation (and then on the parameter .(A)) of AA = 0.13 at 100 Mrad. Comparing the fits for different periods of irradiation, we have estimated the relative systematic error Ap/p to be 0.03 at 450 nm and 0.08 at 610nm. As observed with the ratios of normalized spectra, the two types of SSU quartz gives different attenuations. The noticeable difference at 450 nm becomes large at the absorbtion bump of 610 nm. Below are the means over the two sets of quartz fibres “G” (1,3-6,8,9) and “R” (2 and 7) “G” < ( ~ ( 4 5 0>= ) 1.52 f 0.02 dB/m < ( ~ ( 6 1 0>= ) 6.08 f 0.04 dB/m “R” < ( ~ ( 4 5 0>= ) 2.11 f 0.04 dB/m < ( ~ ( 6 1 0>= ) 11.89 f 0.04 dB/m 3.3. Mechanical Strength of Fibres The mechanical strength of three types of irradiated fibres was measured. Twenty masurements were carried out for each type of fibre. The results are given in Table 2. There is no significant radiation effect on the tensile modulus. The PT fibres present the highest tensile strength with minumum RMS. 4. Discussion and Conclusions
We performed a set of tests for the mechanical and optical properties of nine types of fused-silica core fibres. We measured in situ the darkening, while irradiated, and the recovery of two fibres after the irradiation. This arrangement allows a direct comparison of the optical properties of two different fibres that is independent of dose, injected light or electron beam fluctuations. There is no significant difference in the optical properties of the polymerclad (qp) fibre drawn by Polymicro Technology and the fluorine doped silica
526
0
I
0.2
"
'
~
Number of electrons (X10'') 0.6 0.8
0.4
'
"
~
"
'
"
"
~
"
'
~
1.2
1
"
'
~
l
Figure 2. Relative transmitted spectra versus dose for fibre (no 4). (a-) at 450 nm and (b) a t 610 nm bandwidth. The curves through the points correspond to the fit with the function 4.
Table2. Fibre tensilestrengthvalues aregiven inGpa. In parentheSis are the minimum and maximum measured values over 20 measurements per sample. Fibre type
No irradiation
30 Mrad
lOOMrad
300 Mrad
2 qq (PT)
4.5f0.6
4.2f 0.6
4.3f 0.6
4.7k 0.4
(2.5,5.1)
(3.2,5.1)
(2.6,5.0)
(3.9,5.2)
4.9 AZ 0.5
5.1 f 0.6
(3.6,5.2)
(3.5,5.5)
3 qq (PT) 5 qq (PT)
1.6 k 0.8
1.7f 0.9
2.2 f 0.8
1.9 f 0.7
(0.5,3.0)
(0.5,2.9)
(0.4,2.9)
(0.4,2.9)
clad fibres drawn by Polymicro or Hesfibel from Heraeus preforms under irradiation up to 100 Mrad. The quality of the core material strongly affects the fibre performance. We measured very different attenuation in fibres drawn, by a single company
527 20
I
I T 1
0
2
0
3
A 4 0
5
L
0
Figure 3. The results of fits with function 4 are shown for the a(X) parameter for the five 300prn core diameter fibres. The a(X) values correspond to the relative attenuation at 100 Mrad.
(Polymicro), where the preforms came from two different suppliers (Heraeus and Russia). The attenuation and recovery as a function of time are well represented by two-parameters fits given by Griscom4. Tensile strength measurements show that Polymicro fibres exhibit the highest tensile strength with minimum RMS. There is no significant radiation effect on the tensile modules, which remains at 4.6 f 0.4. Three bands of luminescence are observed in fused silica at 280nm, 470 nm and 650 nm with lifetimes around 4 ns, 2-10 ms, and 2 0 p , re~pectively~3~. The characteristics of the luminescence, mainly the 470 nm band, in the fibres have to be further measured in order to evaluate fully the effects of the luminescence on the performance of the HF calorimeter.
Acknowledgments We thank Louis Rinolfi, Simon Baird and the LIL operators for the delivery of a high-quality electron beam; Bernard Amacker for the connector and fibre
528
L 0
Figure 4. The same fitting procedure as in Figure 3 results in determination of the parameter for same 300prn core diameter fibres.
p(X)
installation; Andre Braem for providing optical components; Minna Santaoja, Hugo Munoz, and Marc Tavlet for the dosimeter measurements; and Florence Pirotte, Andre Muller, and Guy Roubaud for safety controls. We also thank Thomas Ruf (LEP) and Emmanuel Tsesmelis (CMS test beam) co-ordinators. This work was supported by the US Department of Energy (DE-FG0291ER 40664) and NSF (NSF-INT-98-20258), the Hungarian National Fund (OTKA T026184), and the Scientific Research Council of Turkey, TUBITAK). References 1. THE COMPACT MUON SOLENOID Technical Proposal, 1994, CERN/LHCC 94-38. 2. N. Achurin et al., Nucl. Instrum. Meth. A399, 202 (1997). 3. K. Becker, Solid State Dosimetry C R C Press., 334 (1973). 4. D.L. Griscom et al., Phys. Rev. Lett. 71,1019 (1993). 5. L. Skuja, J. Non-Crystalline Solids. 239, 16 (1998). 6. A.L. Tomashuk et al., IEEE Frans. Nucl. Sci. 47, 693 (2000).
Scintillation Calorimetry Covener: M. Cavalli-Sforxa
M. Cavalli-Sforza
Covener’s Report
A. Henriques
Status of the ATLAS Tile Hadron Calorimeter Production
S. Nemecck
Studies of the ATLAS Tile Hadron Calorimeter Performance
S. Katta
An Overview of CMS Central Hadron Calorimeter
A. Benen
Performance and Calibration of the Forward Plug Calorimeter at ZEUS
A. Attal
Plug Shower Maximum Detector for CDF Run I1
S. Dell’Agnello
CDF I1 Integrated Calorimetry Environment
L. Miramonti
Borexino: A Real Time Liquid Scintillator Detector for Low Energy Solar Neutrino Study
L. Mualem
The MINOS Far Detector Construction and Quality Assurance Testing
S. White
A New Hermetic Electromagnetic Calorimeter Design for Future Collider Experiments
V. Korbel
The Tile HCAL Calorimeter for the TESLA Detector, a Status Report
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SCINTILLATION CALORIMETRY
MATTE0 CAVALLI-SFORZA IFAE, Universitat Autonoma de Barcelona, E-08193 Bellaterm (Barcelona), Spain E-mail: caval1iOifae.es (Convener’s Report)
Scintillation Calorimetry remains to-date a popular and cost-effective technique to create large calorimeters a t colliders, stationary-target facilities, and solar neutrino observatories. While sampling calorimeters - usually with WLS fiber readout - represent the greatest majority of the entries, fully active calorimeters for the very low-energy solar neutrinos are also present. The ten contributions that appear in this session indeed represent a broad variety of detectors, spanning the range from the upgrades of the more mature facilities to major calorimeters currently under construction, but also including conceptual studies and prototypes for future machines. To the first category belong the Zeus Forward Plug Calorimeter, presented by Arno Benen, the Plug Shower Maximum Detector for Run I1 of CDF, described by Alon Attal, and the comprehensive report by Simone dell’Agnello on the CDF2 Integrated Calorimetry Environment. The Liquid Scintillator Detector of the Borexino experiment - an unsegmented, fully active detector, was described by Lino Miramonti. The work in progress on an other calorimetric neutrino detector, for MINOS, was reported on by Leon Mualem. The sampling techique was chosen by both general-purpose LHC experiments, ATLAS and CMS, for their massive hadronic calorimeters in the lowto-moderate 77 regions. Ana Henriques and Stanislav Nemecek (standing in for Ilya Korolkov) showed the construction and testing activities of the ATLAS Tile Calorimeter, while Sudhakar Katta covered these aspects for the CMS Central Hadron Calorimeter. Finally, addressing the requirements of hermeticity, high segmentation and energy-flow performance of the next generation of calorimeters for future colliders, Sebastian White showed the design of a hermetic electromagnetic calorimeter, while Volker Korbel reported on the R&D work in progress and test program on a hadronic calorimeter prototype.
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STATUS OF THE ATLAS TILE HADRONIC CALORIMETER PRODUCTION
A. HENRIQUES CERN CH 1211 Geneva, Switzerland E-mail: ana.henriguesOcern.ch (For the ATLAS Tilecal collaboration)
The status of the construction of the ATLAS TILECAL hadron calorimeter is reported. The various aspects of the construction started at the end of 1998: mechanics, optics, instrumentation, certification and final integration will be presented. At present 80% of the 3 cylinders: 1 barrel and 2 extended barrels is fully instrumented and stored at CERN. Various quality control steps are done during the components production and during the modules instrumentation. An evaluation of the modules uniformity extracted during the final certification using a radioactive 137Cssource is shown. The status of the electronics production and the modules performance extracted during the calibration with particle beams are described in other talks of this conference presented by M.Varanda, F.Martin and S. Nemecek.
1. Calorimeter design
The ATLAS Barrel calorimeter will include a Pb-Liquid Argon (LAr) electromagnetic calorimeter with accordion-shaped electrodes, and a large scintillating Tile hadronic calorimeter, with iron as absorber material and scintillating plates read out by wavelength shifting fibres. The iron to scintillator ratio is 4.67 to 1 in volume. The main function of the Tile Calorimeter is to contribute to the energy reconstruction of the jets produced in the pp interactions with an energy resolution of 5 0 % / 0 3% and, with the addition of the end-cap and forward calorimeters, to provide a good p ~ measurement. ~ i ~ ~ The Tile Calorimeter consists of a cylindrical structure with an inner radius of 2280 mm and an outer radius of 4230 mm. It is subdivided into a 5640 mm long central barrel and two 2910 mm extended barrels as shown in Figure 1 a. The barrel covers the region -1.0< 1771 2.
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622 1.2. Micromodule
The CMS Preshower detector consists of two layers of lead converter and silicon strip sensors. The strips of the two planes of silicon sensors are orthogonal to each other. The sensor size is 6.3 x 6.3cm2 with 32 strips at 1.9 mm pitch and 320pm thick3. The basic detection unit, a micromodule, consists of a silicon sensor and the front-end readout electronics, both mounted on a ceramic substrate and an aluminium holder for mechanical support (Figure 1)2.
\bias
i
voltaqe
i
Figure 1.
The micromodule and its components.
2. Front-end electronics: PACE2 The front end electronics4 includes two chips: the preamplifier and shaper chip, Delta, and the analog memory and multiplexer chip, PACE-AM (Figure 2). Having two chips helps reduce any coupling between the digital part of the PACE-AM chip from the sensitive analog Delta chip. These chips are made in 0.8 pm BiCMOS DMILL technology with requirements for radiation hardness of up to lOMrad of ionizing radiation and up to 2 x 1014n/cm2 of neutron fluence.
623
I
I
PACE 2
I
Figure 2.
Block diagram of the PACE2 assembly.
Delta chip has 32 channels of preamplifier with leakage current compensation. Due to the harsh radiation environment, the silicon sensors will have increasing leakage current after few years of running. The preamplifier is DC coupled to the silicon sensor and can compensate for leakage current up t o 150pA. The CR - RC2 shaper is designed to have a peaking time of 25ns and can be switched between two gains. The low gain (LG), with a dynamic range up to 400 MIPs (minimun ionizing particles) is used for physics data taking while high gain (HG), with a dynamic range up t o 50 MIPs is used for absolute calibration of the MIP using particles and pulse injection. There are also 9 programmable DACs for internal biasing and current settings and calibration. Since the biasing condition changes with radiation dose, the biases and currents can be tuned by changing the appropriate DAC value, thus maintaining optimal performance. A calibration DAC is used to inject charges across the whole dynamic range and to cross-calibrate the two gains. PACE-AM contains a 32 channel wide, 160 cell deep analog memory (switched capacitor matrix). Signals from the shaper are sampled at 40MHz into cell memory specified by a write pointer. A read pointer, separated from the write pointer in time by the trigger latency, is used t o block 3 consecutive time samples when the level 1 trigger arrives. These blocked cells are read by an amplifier, multiplexed out at 20 MHz and then digitized externally by an ADC. The output signal is divided by 2 in order t o fit the 1V dynamic range of the ADC. The PACE2 chips were submitted at the end of 2000 and received in Spring 2001. A special motherboard was built containing the ADC (Analog Device 9042) t o digitize the serial data, an FPGA (Altera FLEX 10k) t o generate
624
all necessary fast signals to the PACE2 chip and a microprocessor (Mitsubishi M16C) t o control PACE2 and to interface with a P C via RS232. This set-up is self-contained and simple to use since it does not require complicated and expensive VME and NIM crates.
2.1. Initial Perfonnace Initial measurements were done on the chips without bonding to a silicon sensor. Digital functionality was checked. Some minor bugs were found but these did not affect the functionality. After fine tuning the biases and currents of the chips, the analog pipeline memory uniformity was measured. Figure 3 a shows the pedestal values for a few channels vs. memory cell number. The pedestal variation has an RMS spread of around 10 ADC counts (2.5mV). They have a similar shape, differing mainly in the overall DC shift. This can be easily corrected with look-up tables (Figure 3 b) .
Figure 3. a) Pedestal vs. memory cell number for a few input channels. b) Solid line: pedestal variation vs. channel before any correction. Dashed line: pedestal variation after applying cell-to-cell corrections.
The gain and signal-to-noise ratio (S/N) can be measured by injecting calibration pulses into the input of the preamplifier. For a fixed memory cell, we obtain 15.8mV/MIP for HG and 2.3mV/MIP for LG with a noise of l.OmV for HG and 0.5mV for LG. This results in S/N ratios of 15.8 (HG) and 4.6 (LG) respectively. By varying the delay of the trigger, we were able to map the pulse shape. The rise-time (10%-90%) is 15.5ns for LG and 18ns for HG. The shaping time is roughly 25ns, satisfying the design.
625
2 . 2 . Performance with Silicon Sensor and Radioactive Source
We have bonded a Preshower silicon sensor to the PACE2. In order to study the real response to particles, we placed a lo6Ru source in front of the sensor and two small plastic scintillators behind to act as a trigger. The single MIP signal was measured in HG (Figure 4 a ). The noise is larger than without a sensor (7 ADC counts=1.75mV instead of lmV), due to the large capacitance loading (52pF) and noise pick-up. A S/N ratio of 5.6 was obtained. This can be improved by better grounding and by using the 3 time samples. Knowing the absolute calibration from the radioactive source, we can inject charges to simulate large numbers of MIPs. The gain is measured (the slope of the straight line fit) to be 9.4mV/MIP (HG) and 1.4mV/MIP (LG). The gain remains constant within the dynamic range of 400 MIPs for LG and 50 MIPs for HG (Figure 5).
+
0.0813E-01 6.W f 233.4 f
0.5710E4.7 0.6959603 0.46Y9E-01
40
60
Figure 4. a) Pedestal and MIP signal from radioactive source fitted with two gaussians. b) Pulse shape for the MIP signal. Both are in HG.
We again mapped-out the pulse shape (Figure 4b). The rise time is around 20ns, slightly slower than the case without silicon but still satisfactory. 3. Conclusion and Outlook
The PACE2 was designed to be used to read out the silicon sensors of the CMS Preshower detector. Analog performance has been measured. One iteration is still needed to correct minor bugs and to extend the length of the analog memory from 160 to 192 in order to give sufficient safety margin for the level 1 trigger latency. Because of the uncertainty in the yield of the DMILL technology, a parallel development in .25 micron technology has started.
626
,
4w Injeclim [MIPs]
0
20
40
I
I
,
60 bljrcrmn [MIPS]
Figure 5. Output pulse height vs. injection signal for a) low gain and b) high gain. The flatten response above 400 MIPS in a) is due to ADC saturation from the high value of the pedestal which can be reduced easily.
References 1. D. Barney et. al. An artificial neural net approach to TO discrimination using the CMS Endcap Preshower, CMS Note 1998/088, (1998). 2. P. Wertelaers et.al. CMS Preshower EDR, CMS ECAL EDR-4 vol. 2, (2000). 3. A. Peisert, N. Zamiatin, Silicon sensors for the CMS Preshower, NIM A479,265 (2002). 4. P. Aspell, Conception et mise au point d e l'e'lectronique frontale du de'tecteur de pied de gerbe (Preshower) de l'expe'rience CMS, thesis, Universite Claude Bernard - Lyon 1, (2001).
THE FRONT-END ELECTRONICS FOR LHCB CALORIMETERS
DOMINIQUE BRETON Loboratoire de I’Acce‘lCrateur LinCaire - Centre Scientifique d’Orsay - B.P.34 - 91898 ORSAY CEDEX, FRANCE
For the readout of the calorimeters of the LHCb experiment at CERN, specific front-end electronics have been designed. In particular, three different front-end analog chips were studied respectively for the ECAL/HCAL, Preshower and Scintillator Pad Detector. We will present the three front-end electronic chains, point out their specific requirements together with their common purpose, and describe the corresponding ASICs.
1. INTRODUCTION The LHCb calorimetry is based on an electromagnetic and an hadronic calorimeter (ECAL/HCAL), a Preshower (PS) and a Scintillator Pad Detector (SPD). This set of four detectors takes place between M1 and M2 muon chambers. It provides high transverse energy hadron, electron and photon candidates for the first level trigger which makes a decision 4 us after the interaction. Its other essential function is the detection of photons to enable the off-line reconstruction of B-decays. These physics goals define the general structure of the calorimeter system and its associated electronics in terms of resolution, shower separation, selectivity and fast response. The ECAL and HCAL are lead-scintillator and iron-scintillator sandwiches read by light shifting fibers. The output of the plastic fibers is equipped with phototubes. The readout system will have about 6000 channels for the ECAL and 1500 for the HCAL. For economic reasons the ECAL and HCAL calorimeters will be equipped with the same electronics including fibers and PMs. The PS and the SPD are pad detectors read by the two ends of a simple fiber and multi-anode PMs. Both have 6000 channels. The crates and the backplanes will be the same for the four detectors, whereas the front-end electronics will be specific for a part and common for the other part.
627
628
2. REQUIREMENTS
The main requirement for LHCb electronics is the pile-up rejection. To ensure a satisfactory independence of successive sampling, it implies fast fibers, fast PMs and fast shaping. In ECAL/HCAL, the shaped signal has to be sampled at 40MHz over 12 bits to cover the resolution over the full dynamic range of the two calorimeters (100 Mev to 10 Gev of transverse energy). Data is then transcoded into energy over 8 bits for trigger data and 12 bits for readout data. The latter has to be buffered during the LO latency of 4psec, derandomized and then rebuffered for the level 1 latency of 256 psec'. The corresponding maximum rates are lMHz for the level 0 and 40kHz for the level 1. After the level 1 trigger, an extended zero suppression has to be performed before sending the formatted event to the DAQ. The aim of PS is twofold: for the level0 trigger, it has to perform the identification of electrons and photons while rejecting the charged pions. In parallel, it has to measure the part of energy lost in itself to correct for the global calorimeter information. The SPD has to perform the separation between photons and the charged particles. There are consequently trigger elements sitting in the front-end crate. The first stages concern the search for local energy maxima inside groups of 512 channels, with a validation by the PS and SPD data. The main difference in the shape of the signals outing the different subdetectors is actually due to the mean number of photoelectrons at their source. The SPD and PS that have to cover the 1 to 100-MIPS range receive only 20-30 photoelectrons per MIP. Their signal is consequently very unpredictable, especially at low levels. Conversely, in the HCAL, we get 50 photoelectrons per GEV, whereas it even goes up to 500-1000 in the ECAL. So they offer a much smoother and reproducible shape. The overall consequence is that the analog front-end electronics will greatly differ among the different sub-detectors. Its description is the aim of the following chapters.
3. FRONT-END OVERVIEW The front-end electronics will be situated on the top of the calorimeters as shown on figure 1. The total radiation dose expected there is about 1-2 krads over 10 years thus allowing the use of commercial components, provided that the most critical of them have been tested in a beam. 14 ECAL and 4 HCAL crates receive respectively 6000 and 1500 channels. 8 P S crates receive a total of 6000 channels both from the PSs and the SPDs very front-end elements. Figure 2 describes the principle of the front-end setup and presents a standard calorimeter front-end crate and its main interconnections. The ECAL/HCAL PM signals are connected to the front-end boards
629
Figure 1. overview of the LHCb detector and location of the calorimeter electronics)
Figure 2. overview of the front-end elements and of the front-end crate
through 10 meters of coaxial cables, whereas differential pairs are used for PS/SPD. There are 16 FEBs in the crates, each receiving 32 signals for ECAL/HCAL crates and 64 from each detector for PS/SPD crates. The output of these boards are connected to the standardized custom backplane, sending signals using LVDS levels to the Calorimeter Readout Controller (CROC) and the Validation boards. The CROC performs the event formatting after the first trigger level. Data is then sent to the DAQ through optical links. The CROC also receives the ECS2 and the TTC signals and therefrom distributes clock, global commands and the serial link that is used for loading the hardware over the whole crate. From its 32 signals, and using also neighboring cells, each ECAL/HCAL FEB computes, in pipeline mode, the maximum of the 32 sums over every 2x2 cell area3. This maximum is sent to the Trigger Validation Board assuming 8
630
FEBs for one Validation. The PS and the SPD validate the ECAL candidates. The energy of the latter is then added to the corresponding HCAL candidates. The output is sent to selection crates via optic links to get the highest (and second highest) of the candidates, for each type of particle. 4. THE FONT-END ELEMENTS OF THE ECAL/HCAL As explained here above, the purpose of those elements is to shape the PM pulses in less than 25ns to avoid electronics pile-up. The corresponding requirements are the following4: 0
0 0
0 0
At the PM output, the maximum current is 20mA over 25 ohms. At the ADC input, the dynamic range has to be 1V under 250 ohms. The residue after 25ns should be smaller than 1%. The sampling area should cover f2nsec with a 1%precision. The RMS noise should be < 1 ADC count (250uV)
To fulfill the requirements listed here above, two problems had to be solved. The first one concerns the PM signal. If one looks at figure 3, which shows a PM signal, the PM output current has a fast rise time but a slow decay that goes over at least the two consecutive samples at 40 MHz. It thus needs to be pulled to zero after 1Ons to ensure the zero pile-up requirement. The remaining area is on the order of 60% of the original one. To realize this cut on the signal, the clipping circuit of figure 4 will be used. I
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It consists in a short 5ns cable located at the output of the PM base. The latter sends part of the signal towards a variable network, which will send back an inverted part of the signal. As both the source and reflected signals are, on average, negative exponential, their superposition gives an almost zero signal, as shown in blue line on figure 3. Now that the input signal has been shaped, we have to measure the energy deposited in the calorimeter. The corresponding
631
Figure 4.
ECAL/HCAL front-end electronics.
information is the area of the PM signal. The best way to measure it without deteriorating too much the statistic fluctuation is to integrate this signal in a capacitor (Cf) as shown in figure 5. The difficulty then becomes to empty this capacitor. Two ways are possible: Use a switch mounted in parallel but this system induces a dead time when the capacitor is being emptied, which implies the use of two integrators in parallel and of a multiplexor. But due to the inevitable injection of charge from the switches, pedestals are generated which can be the sources of drifts at the 0.1% level. Subtract in a linear way the signal to itself thanks to a specific configuration. The latter was the chosen solution. The corresponding configuration appears in the middle of figure 4. The input signal of the analog chip is diverted, delayed by 25ns, then subtracted to itself thanks to the differential buffer. The latter also has in charge the division of the input current to adapt it to the small value of Cf. This solution is the one formerly proposed in the technical proposal2. Between the buffer and the integrator, an external AC coupling allows us to separate the DC levels. The integrator has a fast rise time and offers a satisfactory plateau at the top of the signal. Physically, as shown on figure 5, the main data path inside the board starts with the four 8-channel coaxial input connectors. The signal goes into the cable compensation, a pole zero network compensating for a 10% -20nsec signal tail, before entering the analog chip. At its output, after the 12bit ADC conversion, data undergoes a subtraction of the smallest of the two previous samples. This subtraction is intended to reduce the high bandwidth noise of the integrator that is never reset, and the two samples are used to decrease the probability
632
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-One channel
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Figure 5. ECAL/HCAL front-end physical implementation
.
that a signal is present in the sample that is subtracted. This subtraction is performed at 40MHz. Figure 6 shows the schematics of the chip. It consists of a differential input buffer that supplies the two opposite charges to the integrator. The buffer is linked to the integrator by an AC link, which is at the same occasion a filtering network. The integration capacitance value of 4pF was chosen for noise reasons. The feedback resistor is a dynamic circuit that provides a high resistance (ICON). The buffer gain was chosen in order to get 1.4V of dynamic range at the output. Its collector 2k resistor, which is used for replacing a 1.5mA current source, was chosen in order to reduce noise and simulate a current output as well as possible. The integrator is based upon a very low noise cascode amplifier with an open loop gain of 65dB. A first output emitter follower is integrated in the chip whereas a second one is mounted on the board with discrete components. This aims at avoiding any feedback from the ADC input to the amplifier, in particular to get rid of any potential saturation at high signal levels. Table 1 shows the performances of the chip. These results show a good adequation between simulation and real circuit, except for the gm of the input transistor. This is due to simulation models and also explains the mismatches in the rise time and the input impedance of the integrator. Figure 7 offers both a view of the 4-channel chip layout and a picture of the board. On the left side of the latter, one can see the 2 x 8 channel input connectors, followed by the PM and cable compensation networks and the delay lines. The four 4-channel analog chips are followed by half the ADCs and LUTs. All the big FPGAs (10K50 and 6K16) which perform the pedestal subtraction and the readout buffering are actually located on the other side of the board, together with the other half of the ADCs.
633 INTEGRATOR Vdd
Vdd
External AC coupling I
I
BUFFER VhS
Figure 6. ECAL/HCAL chip schematics Table 1. Chip performances
Integrator open Loop
65dB
6538
gain Crosstalk
_&
0.");
Figure 3. Energy spectrum of all channels, corrected and uncorrected, 2000 (left) and 2002 (right) data.
4.3. Linearity
The electronic calibration corrects nonlinearities of the preamplifier response. However, at first the EMC data still showed nonlinear behavior in certain energy windows (left of Fig. 3) which had to be corrected offline. This effect resulted from the overlay of three independent problems. A curcuit on the ADC board could be driven into an oscillating state when the board was running under high load, for example during an electronic cdibration when all channels fire simultaneously. This was the strongest contribution to the observed nonlinearity and required energy corrections of up to 10%. In the 2000/2001 winter shutdown all ADC boards were modified to remove the oscillation. The second largest contribution ( 5 4% correction) turned out to be crosstalk between neighboring channels, propagating through the preamplifier cable shields. It is now corrected for as part of the electronic calibration procedure. The crosstalk pattern was surveyed for every channel inside an ADC board and its neighboring boards during the 2000/2001 shutdown. As part of the calibration, the magnitude of the crosstalk is determined by pulsing only every other channel while reading out the crosstalk signal in the unpulsed channels. The correction is then applied to each channel's calibration according to the pattern expected for this channel, scaled with the magnitude measured as part of the same calibration. After removing these two contributions, the EMC data was left with nonlinearities requiring corrections of up to 2%, however only in very narrow energy windows (right of Fig. 3). They appeared precisely where the range encoding curcuitry switches from one energy range to the next one. The underlying effect is still under investigation, however a correction procedure has been deployed recently which removes the nonlinearity.
663 4.4. Reliability
ADBs replaced
106s replaced
n
TRBs replaced Figure 4. Number of frontend electronics board failures per quarter since October 1999, for ADC Boards (top, serves 12 channels, 560 in system), 1/0 Boards (center, 72 channels, 100 in system), and Transition Boards (bottom, 720 channels, 10 in system).
Only a small fraction of the electronics components - readout diodes and preamplifiers - are not easily accessible. They are implemented in twofold redundancy to allow for at least 10 years of continuous operation without any major intervention. To date, there is only one out of 6580 channels which has been unusable since installation. One of two diodes/preamplifiers has been disabled for 11 other channels. The readily replacable components include ADC boards, 1/0 boards, and transition boards. While the failure rate was substantial immediately follow-
664
ing installation or reinstallation during a shutdown, it has subsided rapidly (Fig. 4). In the first months of operation the fiber optics transmitters were dying at an alarming rate. It was found the vendor had supplied CD lasers, unsuited for continuous operation under BABAR conditions. All transmitters were replaced with vertical cavity surface emitting lasers from a different vendor. After an initial infant mortality of 1% in the first two weeks there has been no failure since. The most common failure modes observed on front end electronics boards so far were, in descending order of occurrence: (1) Multipin connectors where one or many pins were disconnected from their solder pads. This was mostly due to the combination of weak solder joints and mechanical stresses from (un)plugging the connector, or bad alignment of the connector and its counterpart. Reinforcing the solder joints and fixing the alignment remedied this problem completely. (2) Unstable electrical contacts due to faulty solder joints. As was the case above, cold solder joints were a frequent flaw of the manufacturing process, and were easily fixed by resoldering the contact. (3) Failures of individual electronic components, apart from the fiber optics transmitters described earlier, have been limited to a few instances with no particular pattern as to the type of component involved. 5. Conclusion In its first three years of operation, the BABAR electromagnetic calorimeter has overcome a number of initial surprises and teething pains. It is now running in a most stable fashion, with little need for maintenance.
References 1. B. Aubert et al. [BABARCollaboration], The B B A R detector, Nucl. Instr. Meth. A479,1 (2002), SLAC-PUB-8569, hep-ex/0105044. 2. M. Kocian, these proceedings. 3. T. Hryn’ova, these proceedings. 4. W. Wisniewski, these proceedings. 5. D. R. Freytag and G. Haller, Analog Floating-point BiCMOS Sampling Chip and Architecture of the Babar CsI Calorimeter Front-End Electronics System at the SLAC B-Factory, BABAR-Note-285; IEEE Trans.Nucl.Sci.43:1610-1614,1996. 6. http://nun.aps.anl.gov/epics/ 7. B. Shwartz, these proceedings.
H1 CALORIMETER DAQ UPGRADE FOR HERA-I1
DIRK HOFFMANN, PIERRE-YVES DUVAL, CLAUDE VALLEE CNRS
-
Centre de Physique des Particules IN2P3 - Univ. Me'diterrane'e, Marseille, France E-mail: Hoflmann OCPPM.In2p3.fi
The H1 collaboration has performed an upgrade of its data acquisition system for the calorimeters in view of the HERA-I1 programme. A heterogeneous system based on 29K/VRTX, 68klOS9 and Vax/VMS was replaced by an integrated Unix cluster composed of two PPC/LynxOS VME boards and Sparc/SunOS stations, using TCP/IP protocols for inter process communication (IPC) and POSIX standards in general. Software transcription consisted of porting three essential functions: hardware setup, calibration datataking with a high serial data throughput and online datataking which emphasizes low frontend deadtime through a three level buffering by means of POSIX threads and messages. Low performance control tasks were programmed in Perl, the user interface has been written in Java. Although the very frontend electronics remain unchanged, a factor two increase in performance was obtained together with a manifestly improved environment for monitoring and diagnostics.
1. System Context and Environment
1.1. H l Calorimetry The H1 experiment' is a multi-purpose 47r detector, which has measured electron-proton and positron-proton collisions on the HERA-I accelerator since 1992. Since 2000, the accelerator underwent a major upgrade2 with the aim to increase instantaneous luminosity by a factor five and to deliver longitudinal lepton polarization. The detector was modified according to the new conditions around the interaction region, and the collaboration also used the time for further enhancements of the experiment. After the upgrade the Calorimeter Subdetector group henceforth comprises 0
0
0
a Liquid Argon (LAr) Calorimeter, which contains 44,352 cells and covers the major part of the polar angle, a Spaghetti Calorimeter (SpaCal) with 1,300 photomultiplier channels in the backward direction for scattered electron detection a small PLUG Calorimeter in the very forward direction for particle measurements at very low angle, which contains eight tiles for a rough
665
666
0
calorimetric measurement, and the analog readout part of the instrumented iron, called Tail Catcher for the measurement of hadronic shower tails leaking out of the LAr calorimeter, with a total of 3,888 channels.
They are readout by a common data acquisition (DAQ) system, the Calorimeter DAQ3 (CaloDAQ), which delivers in turn the data to the Central H1 DAQ.
1.2. Energy and T i m e Measurement The analog data of in total 49,548 channels are shaped in different electronic equipment, according to their origin and time behavioura. The final digitization for the energy measurement is performed by identical 12-bit ADCs, which are multiplexed, sequenced and read out by a total of 70 custom made DSP boards4 equipped with CPUs of the 56k generation5. Three additional DSPs of the same type treat special detector signals from photodiodes, trigger electronics and TDCs in the SpaCal partition. Certain channels with large signal dynamics are fed to the ADC battery through two amplifiers with different gains, thus allowing for an effective 14-bit precision. A third order polynomial calibration correction and zero-suppression are performed by the DSPs on the fly, without adding overhead to the generic sequencing time of the ADCs. In parallel to the precise and stable energy measurement, the LAr cells are used in the LAr Trigger' branch to deliver fast signals for time measurement and trigger purposes. To this end, all channels are fed into a total of 512 big tower sums according to their geometrical location and separately for the cells of the electromagnetic and hadronic calorimeter parts. Their signals are sampled after fast shaping by 8-bit Flash-ADCs at the HERA bunch crossing rate of 10.4 MHz. They fill a digital pipeline delivering a trigger decision after 2.3 ps, but internally keep a history of 256 bunch crossings. The readout is performed by eleven 56k DSPs, mounted on a different type of custom made VME board7. These are in charge of the calorimeter data transmission to the higher trigger levels and perform the readout of the big tower signal history around the nominal interaction time and the calculation of time weighted energy sums for signal pileup monitoring. The trigger raw data amount to 150 kB, which is comparable to the data volume in the calorimetry ADC branch.
*The pulse length in the SpaCal is of the order of 1 ns, whereas the drift time in the LAr Calorimeter nears the 0.5 ps.
667
1.3. Inter Crate Communication and VME Tree The CaloDAQ readout electronics consist of several hundred boards in VME standard, accommodated in 47 VME crates, which communicate through
17 DSP CALORIMETRY fonvardbmel IR
CALIBRATION
Figure 1. VME tree of the readout electronics in the two CaloDAQ branches: Crates on the left side contain the DSPs of the ADC/TDC branch. DSP crates for the trigger readout are placed on the right. Two big arrows indicate the main directions of the readout data flow. The Event Builder PPCs on top of these arrows feed their data into the Central DAQ Taxi boards, which are linked by an optical fiber ring to the other H I DAQ branches. All VME crates of the frontend electronics are connected by VICbus branches, starting from either of the Event Builder crates. The PPCs are connected to each other and a local Unix cluster fileserver through Fast Ethernet.
668
VICbusg connections on two and three vertical busses respectively in two separate branches. Fig. l illustrates this segmentation into the ADC/TDC branch and the Trigger branch, each equipped with a Taxi' connection to the Central DAQ. The readout hardware properly speaking is completed by crates for setup, calibration, interface to the Central H1 Trigger and monitoring. The address space in this VMEtree is managed by a custom-made VMEtree compiler, which allocates VME pages dynamically and translates the tree into the setup of the master VIC boards. Extensions of the Calorimeters like the Jet Trigger" are supposed to use the faster, smaller and more reliable PVICll connections for the same price. The PVIC setup will be integrated in the VICVMEtree compiler as well, thus providing the option to replace single VICbus branches transparently in future. The Event Builder PPCs are connected to each other and to a local Unix cluster by 100baseT connections (Fast Ethernet) on two Gigabit IP switches, which communicate through a glass fiber backbone. This is the gateway to all other Internet hosts and the switches can isolate the CaloDAQ hosts completely or limit the bandwidth for outsiders, if needed. 1.4. Hardware Choices f o r the Upgmde
The newly installed upgrade parts are hatched in fig. 1;foreseen extensions are shaded in light gray. Two PPCs on a R10212 VME board replace the former3 AMD 29k processors; and a Unix cluster replaces the anterior OS/S-Vax system in the central control. Control and management tasks (cf. sec. 2) have been partly shifted into the frontend, due to significantly higher computing power of contemporary CPUs. All PPCs run the real-time operating system LynxOS13. The extension by the Jet Trigger" project will demand additional capacities in the readout of the Trigger branch, which can be provided through a satellite P P C station on a PVIC'l bus. The Unix Cluster was extended from an existing Sparc station running SolarisOS. It is used as a fileserver for all LynxOS systems and included in the central DESY backup for maximum data integrity. Tests with a Pentium 111 under a recent version of Linux showed that there are no drawbacks when using this lower-priced alternative, except for the different byte order in the CPUs, which might imply some careful rewriting of offline analysis programs. 2. Software Design 2.1. Servers, Clients and Protocols
The Event Builder CPUs can be accessed through Internet protocol (IP). Firewalls and server internal host selection algorithms protect against unwanted
669
accesses. Both Event Builders have an identical client/server program structure (see fig. 2), which enables them to call each other in case of requests which need synchronization. The “entrance” for all DAQ requests is a Unix socket,
Figure 2. Software architecture of the new CaloDAQ for one Event Builder: On request from a DAQ client, the DAQ server daqd can launch one or several service processes, which access the VME bus. Service tasks which send back data, can write into a file, connect in turn to a data receiving server, or dump data into the Multi Event Buffers of the Central DAQ Taxi. The post office process daqpo is explained in the text.
which is bound by the daemonizingb server daqd. Depending on the kind of request, daqd selects VME service programs, which do the actual hardware access. In this way the exclusive access to VME can be granted if necessary. The daqd request protocol is not time critical and therefore plain text, which has proven to provide efficient ways for debugging or test of clients and servers independently from the current status of other parts of the project. Service programs include request for setup (rqs) of the VME boards, request for readout in standalone mode ( r q r ) , expert setup of the LAr Trigger ( t r i g l o a d , ssm) and high performance event building for real time data taking (eb, sec. 3). They are implemented as standalone programs, taking their configuration data from the standard input channel, which allows once more uncoupled (object oriented) testing of single blocks. In case they produce any data for the requester, these are formatted in H1 standard BOSi5 format and sent in binary form through an extra IP channel. As the response of daqd is strictly sequential and prioritized, the task of asynchronous status and error reports between processes has been delegated to the DAQ post office (daqpo) daemon. It allows message exchange in the DAQ through an unlimited number of sockets from various clients with low priority compared to other tasks on the CPU. It broadcasts incoming messages to all connected clients. In addition, daqpo translates Central DAQ run requests ~~
bdetached from its calling (parent) process and running in background, typically started at system boot time
670
coming through the traditional VMEtaxi channel, as long as the IP protocol is not yet implemented there. 2.2. Choice of Pmgmmming Languages
The different elements of the DAQ software have been encapsulated to the most possible extent during design and are only seen by others through their interface definition. This enabled us to choose different technologies according to the aim and the requirements of each of the programs. daqd: modest requirements on reactivity and data throughput on one hand and high flexibility for the implementation of new requests on the other led to the decision for a compiled scripting language, Perl 5 , which is optimal for the recognition of text patterns and reliable for long uptimes. VME service programs: The high demand for performance and the usage of system level C routines made it necessary to use compiled programs for these tasks. The chosen standard for message queues and threads was POSIX'8. daqpo: was designed in the style of all other VME service programs. DAQ Clients: Up to now, and not including the trivial method by a telnet command, three different technologies have been used to design clients for the new DAQ. The main user interface (cf. sec. 4) has been written in Java; a very complex trigger analysis and calibration package had been inherited in FORTRAN and was adapted to the TCP/IP protocol by means of a C wrapper; and some debug clients and receiver servers have been written in Perl. The combination of all programs for the standard electronic offline calibration resulted in a gain in performance of an approximate factor two. This will allow to control and perform the calorimeter calibration more often and more reliably, as the regular idle time of the accelerator without beam is usually not more than 30 minutes.
3. Real Time Behaviour The most challenging project in DAQ systems is the readout part, where optimal performance is needed in interplay with many other systems of the detector. The event building programs of the two CaloDAQ branches are split into three main threads, which are shown in fig. 3 for the ADC/TDC branch'. CThe Trigger branch is designed identically with the exception that DSP and IT routine have three front end buffers.
671
Figure 3. Program threads (in ovals) of the real time event building program, from left to right with decreasing priority: The IT provides the buffering for unbuffered front end registers. The bulk of data is stored in one of two DSP buffers. The BM gathers the primary buffer blocks and writes them to a circular buffer, from where the EB dispatches them among possible consumers after formatting.
As not all frontend hardware contains internal buffers like the DSPs described above, an interrupt routine (IT) is used to readout these registers and hands them over t o the block mover (BM) in two buffers. The BM task acts, when the first order dead time has finished, because at least one front end buffer for the next event is available in the DSPs. It stores the data from the front end buffers into a ring buffer, which can hold approximately twenty events, depending on their size. A third task is in charge of the actual event building (EB), which means data formatting and delivery to the Taxi board of the Central DAQ or optionally a monitoring file or IP client. We recorded fig. 4 as a benchmark for the new CaloDAQ. The slope of the
0.35 7
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m 0.8). The granularity depends on the pseudorapidity q, the azimuthal angle 4 and the
695
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Figure 1.
Detail of the LAr EM calorimeter structure.
depth. The electrodes (see figure 2 on the left) define the granularity in depth (three compartments named front, middle and back) and in pseudorapidity 77. The granularity is thinner in the front than in the two others compartments. The line at 77 = 0.8 is the boundary between the two types of electrodes. Table 1 summarizes the barrel granularity. Table 1.
Granularity in the barrel
r ComDartment I
An
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2~1256
697
Figure 2.
Left: view of a barrel electrode. Right: Sketch of an end-cap module.
2.2. The end-caps
The end-cap3 is composed of two wheels with a projective crack a t q = 2.5. It covers a pseudorapidity from 77 = 1.375 to 3.2 and it is subdivided into 8 modules (See figure 2 on the right). In one module, 96 absorbers and electrodes are stacked in the outer wheel and 32 in the inner wheel. The gap increases with the radius and therefore decreases with 77. Table 2 summarizes the granularity in the end-cap. Table 2. Wheel Outer
Inner
0 range [1.375,1.425] [1.425,1.5] [1.5,1.8] [1.8,2.0] [2.0,2.4] [2.4,2.5] [2.5,3.2]
Granularity in the end-cap Front
Middle
0.05 x 0.1 0.025 x 0.1 0.03 X 0.1 0.04 X 0.1 0.06 X 0.1 0.025 x 0.1
0.05 x 0.025 0.025 x 0.025 0.025 X 0.025 0.025 X 0.025 0.025 X 0.025 0.025 x 0.025 0.1 x 0.1
N
N
N
Back
0.050 X 0.050 X 0.050 X 0.050 x 0.1 x
0.025 0.025 0.025 0.025
0.1
The outer wheel is devoted to precision physics so that it is segmented into three longitudinal sections. The inner wheel is segmented only into two sections. The main difference between barrel and end-cap comes from the high voltage set up. It is constant everywhere in the barrel. The detector signal is proportionnal to the drift velocity and inversely proportionnal to the liquid argon gap thickness so that an 77-independent detector response could be achieved with a continuously varying HV with the pseudorapidity. Figure 3 on the left exhibits this variation of the high voltage with respect to 77 (open circle).For technical reasons, a high voltage varying by steps (full triangle) was chosen.
698
Inner Wheel 0
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2.6
2.8
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20
Figure 3. Left: High voltage variation along residual of step effect: energy versus 11.
I
4
II 7)
for a constant calorimeter response. Right:
Figure 3 on the right shows the raw energy versus the pseudorapidity for the 2001 test beam data. The residual of step effect in each HV zones is not corrected yet. 3. The calorimeter: mechanical components 3.1. The absorbers Table 3.
Components specification for an absorber Barrel TI
< 0.8 I n > 0.8 I
End-cap Outer W. I Inner W.
0.2 mm 0.15 mm adhesive
I absorber The absorbers are made of lead plates jacketed in two layers of stainless stell to ensure the absorber rigidity. These layers are glued using a glass-fibre adhesive. Table below summarizes the thickness of each component. The lead plates thickness changes at 77 = 0.8 in the barrel. To minimize the contribution of the passive material to the constant term in the energy resolution, stringent tolerances on the lead plate thickness must be imposed so that all the plates were thickness mapped using a technique based on ultrasound. Deduced from
699
the r.m.s of the sliding mean thickness, a contribution to the constant term of 0.12% and 0.18% is expected in the barrel. In the end-cap, a raw simulation indicates that a thickness distribution with a r.m.s inferior to 17pm in the outer wheel and 22pm in the inner wheel is required to achieve a contribution of the order of 0.2% to the local constant term. For all measurements, a r.m.s of 9pm was obtained, well below tolerances. In the barrel, for each absorber a 3D measurement is carried. In the end-cap, absorbers are controlled by optical inspection, thickness and width measurements at prefixed positions. For 10% of its, a 3D measurement is carried. Requirements on the liquid argon gap uniformity is at the 2% r.m.s level. Absorbers production goes on normaly.
3.2. The electrodes An electrode consists of three layers of copper, insulated by two kapton polyimide sheets, as shown in figure 4. The outer layers provide the HV while the
i(t)
Figure 4.
Schematic view and photo of an electrode
700
inner one allows the signal collection by capacitive coupling. The granularity in Q and in depht is obtained by etched patterns on the different layers. All resistors and capacitances are measured and a high voltage test is performed. Since module0, the series production have been strongly improved. Now less than 10% of the electrodes are rejected during the fabrication cycle. At the moment more than 80% of the electrodes are delivered. 4. Stacking and Tests
In a cleaned room successively absorber, spacers, electrode, spacers and finally another absorber are stacked (this entire group is named gap). Of the order of 4 gaps a day are stacked. After stacking one gap, the thickness of the stack is measured and a capagap test is carried out. Regularly two electrical tests are ~ e r f o r m e d ~the > ~ low : frecuency test and the high voltage test. Now the nominal HV is applied during the night to bake out. 4.1. Overthickness measuremnents
To control the overthickness of every absorber, the relative heigh of each wave is measured. 4.2. Low frequency test
It allows to check the continuity of the electrical circuit and the electrode connections including the high voltage distribution. A low frequency sinusoidal signals is injected on the HV lines. A current is induced on the signal layer. The decoupling capacitance is calculated.
4.3. High voltage test With this test, any high voltage problem is detected by measuring the leakage current of each electrode side and each high voltage sectors so that the absorbers, electrodes and honeycomb spacers cleanliness are checked as well as any surface default. A tension is applied to the electrodes and the leakage currents are recorded. At the beginning, the charge currents are dominated by the decoupling capacitance charge so that they are roughly constant (they are proportionnal to the sector surface. See equation 1).
Above a given threshold, the voltage is stabilized until a significant decrease of the whole currents.
701 4.4. Gap measurements
This test is carried out to measure the distance between the electrode and the absorber. In the barrel, the gap have to be constant while in the end-cap, they have to be all the sa,me for a given 77. A sinusoidal input signal is injected on one cell. With the measured impedance, the gap capacitance value is deduced. With the production modules, the contribution to the constant term is of the order of 0.2%.
4.5. Cabling
After asembling, the module is fully cabled with summing boards, mother boards and high voltage boards. Summing boards: They group the signal in q5 to the desired granularity.
[
&ell
I
Barrel 16 electrodes
I I
End-cap 12 electrodes
I I
( End-cap OW) 3 electrodes
1 1
+
(Barrel End-cap IW) 4 electrodes
Mother boards: They are connected to the summing boards and they route the output signals to the readout cables and they include precision injection resistors for the calibration system. HV boards: They supply the high voltage to electrodes. Eventually, at room temperature, the following electrical test are performed: a low frequency test and a high voltage test. Then modules are tested at cold (at CERN for the end-cap, at Saclay, Annecy and CERN for the barrel). At the moment 11 modules are already produced in the barrel (first full-equiped half barrel before the end of this year) and 3 in the end-cap (first full end-cap at the end of this year). 5. Uniformity
In figure 5 the energy versus the pseudorapidity in the barrel as well as the energy distribution are represented. The RMS over the mean energy is of the order of 0.9%. The lead plates transition at 77 = 0.8 is not corrected yet and there is X-talk in the testbeam feedthrough. Further detailed studies of elaborating calibration are in progress in order to improve the RMS over the mean energy.
702
245
MODULE M10
240
s
235
W
Q 230
b 225 220 215
10 Figure 5.
20
30
40
0
50
q (middle)
Mean energy versus pseudorapidity.
6. Conclusion
Four series modules have been beam tested so far an three more are expected to be beam tested in 2002. At the moment eleven modules have been produced in the barrel and three in the end-cap. Up to now the production goes on normally. Improvements of analysis are in progress. References 1. ATLAS Collaboration, A T L A S Calorimeter Performance Technical Design Report CERN/LHCC/96-40 2. ATLAS Collaboration, Performance of the Barrel Module 0 of the A T L A S Electromagnetic CalorimeterNucl. Instrum. Meth. A to be published. 3. ATLAS Collaboration, Performance of the Endcap Module 0 of the A T L A S Electromagnetic Calorimeter, Nucl. Instrum. Meth. A to be published. 4. N. Massol et All Test bench of the barrel calorimeter modules ATL-LARG-2001-007. 5. P.Baxrillon et Al, Test bench and R L C measurements of the electromagnetic endcap calorimeter modules to be published.
PERFORMANCE OF ATLAS EM MODULES IN TEST BEAM
D. ZERWAS Labomtoire de I'Acce'le'mteur Line'aire, B.P. 34, 91898 Orsay Cedex, France E-mail: zerwasOlal.in2p3.f r (On behalf of the ATLAS EM Group)
Barrel and endcap modules for the electromagnetic calorimeter of ATLAS have been built and exposed to electron beams of up to 245 GeV. Their performance in terms of noise, energy and position resolution is discussed and compared with Monte Carlo simulations.
1. Introduction The pre-series (module 0) and series modules (barrel: M10, M13; endcap ECCO, ECC1) of the future electromagnetic barrel and endcap calorimeters' of ATLAS have been tested in electron beams at CERN's H6 (H8) beam line with energies from 10 GeV up to 180 GeV (245 GeV). The construction of these modules is described elsewhere2. The goal of the module 0 tests, performed from 1998 to 2000, was the validation of changes since the previous prototypes built and tested in 1997314, i.e., the use of large electrodes, use of lead sheets with a constant thickness in the endcap, cold electronics (summing and mother boards). In the course of these tests, the design of the summing and mother boards was improved and validated. In addition, the test beam also served to validate the ATLASlike electronics (Front End Board, Calibration Board) which are described elsewhere5. The beam tests of the series modules are part of the quality and acceptance control for ATLAS modules. In the following the module 0 results are final, whereas the series module results are preliminary. The paper is structured as follows: first the test beam setup will be described, followed by a discussion of the signal reconstruction. The modules' response to muons and electrons will be presented and compared to Monte Carlo simulations. The results are summarized in the last section.
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2. The Test Beam Setup Each beam line is equipped with four beam chambers. The coincidence of three scintillation counters (in front of the cryostat) is used as trigger. The cryostat can be moved around a virtual ATLAS interaction point to scan the uniformity of the whole calorimeter module. Behind the cryostat muon and pion counters are installed behind about 5 A0 of iron and lead. The dead material in front of the calorimeter is 1.1 (1.4) XOfor the endcap (barrel). In 2001 in the barrel beam line additional material, present since the begin of the tests, due to a incorrectly installed beam tool, amounting to 0.3 Xo was discovered. Data are read through feedthroughs, of which only one has gold-plated pin carriers to operate the transition cold to vacuum and vacuum to warm. The signal was sampled with ATLAS-like electronics installed in the warm on the feedthrough at 40 MHz, i.e., every 25 ns. The signal maximum is reached typically after -40 ns. Seven samples were recorded. As the trigger was asynchronous, the phase of the 40 MHz clock with respect to the trigger was recorded. The variation of the energy response as function of the temperature was measured to be -2%/K. The typical variation of the temperature (89 K) of the liquid over a beam period of two weeks was (rms) 7 mK. 3. Signal Reconstruction
The physics signal is generated in the detector gap, whereas the calibration signal is injected in the mother boards. While most of the signal path is common to the calibration and physics signals, any non-uniform inductance seen in series by the physics signal and in parallel by the calibration signal can affect the uniformity of the module. There are several potential sources of inductance in the calorimeter which were studied in detail: the summing board, which was modified to have equalized inductances in 4, and the electrode. 3.1. Electrical Detector Modeling
The capacity and inductance of the electrode were calculated and compared to measurements with an RLC-bridge. While the measured capacitances agreed quite well in form as function of 17, a disagreement was observed for the inductance of the middle compartment, where the signal is brought to the connector on a thin line past the back section: every 8th cell the measured inductance was greater than the calculated one. The jump was traced to insufficient grounding of the electrode connector: every other connector has the structure (G=Ground return, M=Middle, B=Back) GMBMMBMG, while the other one
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is GMBMMBM. The missing ground return was added subsequently on all electrodes. The effect of the inductance on the calibration and physics signal was studied in a mockup, where holed polypropylene was used instead of Argon. The mockup permitted to inject physics-like (on the electrode) and calibration-like (at the summing board) of input signals of the same amplitude. The inductance, as shown in Figure 1, modifies the signal shape on its rising edge and reduces the amplitude of the calibration signal. Quantitatively, the inductance induces a bias of 0.2%/nH. 3.2. Optimal Filtering
The signal amplitude (Ama,)was reconstructed as a linear combination (digital aiSi). The coefficients ai were filtering6) of five samples in time (Ama, = Efz1 determined from the noise autocorrelation function, the pulse shape and its derivative. The main difficulty was the prediction of the physics pulse shape. As physics and calibration signals share most of the signal path, after a Fourier transformation the common signal path cancels in the ratio of calibration to physics signal. The physics shape then follows from calibration shape by correcting for the different input currents, triangle current for physics and exponential decay for the calibration signal, and the inductance Lo. Only three parameters were needed in this approach: the starting times of the physics and calibration signal and W D = 1 / d m . With this method the shape was fitted with residuals of k2% in the middle
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compartment, even on the rising edge of the signal, where the effect of the inductance is strongest. The measured ratios between physics and calibration amplitudes, typically 4%, showed the characteristic jump every eighth cell (correction 6%) as expected from the insufficient grounding. For the endcap data, an approach based on sigmoid functions and neural networks was used, leading to residuals of about 3~2%. 3.3. Noise performance and Cross talk studies
The noise behavior, after application of the optimal filtering coefficients, was flat as function of 71, except for the back due to the variation of the detector capacitances. The coherent noise per FEB (128 channels) was measured to be less than 5% in high gain. For an electron cluster, e.g., at 77 = 0.26, the noise was determined to be 143 MeV (261 MeV) in high (medium) gain of which 95% (80%) was incoherent noise. Typically the application of OF coefficients reduced the noise by a factor 1.4 to 1.8, depending on the detector capacitance, with respect to a single sample measurement. The crosstalk between the different sections was studied extensively. In the barrel in particular, the crosstalk between front and middle sections (via the High-Voltage-resistors) was stable over the beam periods (cool up and down) and well correlated with the electrode resistances. The crosstalk middle to back (inductive crosstalk) was reduced by the addition of the missing ground return (before: 1%every 8th cell, after: homogeneous at 0.5%). In the endcap the front-front crosstalk was large as expected due to the fine segmentation (capacity). The middle-middle (inductive) crosstalk was measured to be 1-2% in the module 0. However for the series module, the summing and mother boards were redesigned and this type of crosstalk was reduced to typically less than 0.5% 4. Response to Muons
To reconstruct the energy deposited by muons in the calorimeter a cluster of size A77 x A# = 1 x 2 in the middle compartment was used. With the beam chambers the impact point in the calorimeter was predicted. The signal to noise ratio was measured to be 7.11 f 0.07. In Figure 2 (Left) the variation of response over one physical gap is shown. The peak to peak variation is about 6%, which is due to the variation of the electrical field in the gap (folds). Using the OF-coefficients for muon signal reconstruction (Figure 2 (Right)) improved the uniformity in 77 with respect to a single sample reconstruction. Thus the muon analysis confirmed that the determination and correction for the inductance is well under control.
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5. Response to Electrons The electron energy was reconstructed in a cluster of size Aq x A 4 = 0.075 x 0.075 in the barrel and Aq x A$ = 0.125 x 0.125 in the endcap (due to the smaller geometrical cell size). The cluster was centered on the most energetic cell in the middle compartment. The weights applied to the presampler and back compartments’ response to compensate for energy losses in front of the calorimeter and leakage were determined by minimizing (TIE. The weights vary as function of q between 6 and 8 for the presampler and for the back from 1.5 to 2.5 for a barrel module. In the endcap, the setting of the high voltage by finite sectors induces a slope of the energy response in a sector. The slope was corrected for with a linear correction as function of q. The correction coefficient was obtained by the minimization of a / E in a HV-sector. The energy was then corrected for lateral leakage in q and 4. The 4 accordion shape induces a modulation of the response. Due to the particular geometry of the endcap, this modulation changes as function of q as shown in Figure 3. The effect is well reproduced in simulation. A residual dependence of the response as function of the phase with respect to the 40 MHz clock was also corrected for.
5.1. Energy Resolution The energy resolution as function of the energy is shown in Figure 4. The noise was subtracted at each energy point. The back section was not used for beam
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energies less than 40 GeV. In the barrel the sampling term was less than 10% in three points ( q < 0.8) and the constant term was less than 0.3% in two of the three points. The energy leakage at q = 0.0875 degraded the constant term to 0.5%. Similar results were obtained with the series modules. For the endcap data, (Figure 4 (bottom)), a sampling term of 10.4% in data, compared with 10.1% in simulation was obtained at q = 1.9. The measured local constant term of 0.3% was in good agreement with the 0.4% expected from simulation. In all other positions, where energy scans were recorded, the local constant term was less than 0.6% and the sampling term better than 13%. The prediction of the absolute energy scale from simulation was correct at the level of 5%. The linearity is better than hl%,for the barrel partially affected by the additional material upstream of the calorimeter. 5.2. Position and Angular Resolution of the Endcap module
To reconstruct the position resolution in the endcap module 0 the energy weighted barycenter was calculated. In the front section in q only three cells were used. The S-shape was corrected for and the beam chamber resolution (about 0.35 mm) was subtracted. The position resolution of the front section was stable, essentially independent of q at 2.7 m m / a as the granularity varies. The position resolution of
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the middle section improved as function of q (Figure 5) from 8.3 mm/& to 3.3 m m / a due to the decrease of the physical cell size. The two measurements of q were combined with the longitudinal shower barycenters to determine the resolution of the polar angle. The beam dispersion of 0.1 mrad was negligible. At q =1.9, 50 m r a d / f i were expected from simulation and achieved. In R4 direction, only the middle was used, as the granularity of front section is too coarse. The position resolution showed the same qualitative behavior as the q resolution. At q = 1.6, 6.5 mm/& were measured and at q = 2.4, 3.2 m m l a were obtained.
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5.3. Uniformity
The uniformity of the energy response of the barrel series module M10 is shown in Figure 6 . The response is flat as function of q even in the transition region (7 = 0.8) of the two lead thicknesses. Deduced from one measurement per middle section cell, the global constant term was determined to be 0.93%, in agreement with 0.94% deduced from the fit of the energy distribution of the whole module. For ATLAS a global constant term of less than 0.7% is required. This is to be achieved by obtaining regional constant terms (AT x Ad = 0.2 x 0.4) of less than 0.5% and inter-calibrating these regions with Z boson decays. This has been achieved in module M10 for several regions of Aq x Ad = 0.2 x 0.15 in the gold plated feedthrough. The module 0 barrel uniformity in Aq x A$ = 1.2 x 0.075 was measured to be 0.8%. For the endcap module 0, the uniformity of the inner wheel was determined to be 0.6%.
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Left: Energy response as function of 7. Right: Energy spectrum module M10.
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6. Conclusions and Perspectives
Since 1998 extensive beam tests of module 0s and series modules have been performed. The hardware (summing boards, mother boards, ground return) has been improved and the ATLAS-like electronics have been validated. In the barrel modules the signal to noise ratio for muons was measured to be 7.11f0.07. A sampling term better than 10% was obtained. The local constant term is less than 0.3%. Preliminary results on the uniformity of the series module are encouraging. The sampling term for the endcap module 0 is less than 13%. The angular resolution is in agreement with ATLAS specifications. A global constant term of 0.6% was obtained in the inner wheel. In 2002 two modules of second half-barrel and one module of the endcap will be tested in beam tests. A combined run of an endcap module and a hadronic endcap module will take place at the end of the year. Combined runs of endcap and forward calorimeter modules and of a barrel module with the hadronic barrel calorimeter (tiles) will be done.
Acknowledgments The author would like to thank the organizers for the well organized conference. It is a pleasure to thank my ATLAS-Larg-EM colleagues for providing me with figures and results. I am indebted to Laurent Serin for discussions in the preparation of the talk and the manuscript.
References 1. ATLAS Collaboration, Liquid Argon Calorimeter Technical Design Report, CERN LHCC/96-41. 2. S. Rodier, these proceedings. 3. RD3 Collaboration, Nucl. Instr. and Methods A411 313 (1998). 4. RD3 Collaboration, Nucl. Instr. and Methods A389 398 (1997). 5. E. Ferrer-Ribas, these proceedings. 6. W.E. Cleland, E.G. Stern, Nucl. Instr. and Methods A338,467 (1994).
THE ATLAS HADRONIC ENDCAP CALORIMETER
M. FINCKE-KEELER University of Victoria, Dept. of Physics and Astronomy Vzctoria B . C., V8 W-3P6, Canada E-mail: mgfOuvic.ca
(For the ATLAS HEC Collaboration)
The construction of the ATLAS Hadronic Endcap Calorimeter is nearing completion. Beam tests of the series modules have been completed. The performance of the modules yields a resolution for electrons of o ( E ) / E = (21.4 f 0.2)%(GeV)1/2/v% @ (0.3 f 0.2)% and for pions of a ( E ) / E = (70.6 f l.5)%(GeV)1/2/v%@( 5 . 8 f 0 . 2 ) % ,where @ denotes a quadratic sum. The uniformity and linearity have been verified. The details of the electronic readout chain are well understood and allow precision predictions for the performance of the calorimeter under the final ATLAS operating conditions.
1. Design of the hadronic Endcap Calorimeter
The ATLAS experiment for the LHC has chosen liquid argon (LAr) as the active material for its endcap calorimetry. The Hadronic Endcap Calorimeter (HEC) will be sharing the endcap cryostat with the Electromagnetic Endcap Calorimeter (EMEC) and the Forward Calorimeter (FCAL). The HEC is a Cu/LAr sampling calorimeter, constructed of 2 wheels at each end with 32 wedge-shaped modules in each wheel. It will cover a range in pseudorapidity of approximately 1.5 < 1771 < 3.2, and both wheels together are designed to provide a nuclear absorption length of 1OX in depth. The modules for the front (rear) wheel consist of layers of 25 mm (50 mm) thick copper separated by liquid argon gaps of 8.5 mm thickness. The gap size is maintained by stainless steel spacers. Each gap is instrumented and further divided with 3 polyimide boards, resulting in 4 subgaps that form an EST structure' (see Fig. 1). The size of the subgaps is maintained by honeycomb mats of a nominal thickness of 1.85 mm. All polyimide boards have an outer carbon-loaded layer that hold the operating HV of 1800 V for the 4 subgaps. The central board is a sandwich that contains a copper-pad readout structure in between the outer polyimide layers. This readout structure defines the granularity of the calorimeter to be Aq x A$ = 0.1 x 0.1 for a pseudorapidity less than 2.5 and
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Figure 1. Artist’s view of a HEC module and a close-up of the substructure of a liquid argon gap.
Aq x Ad = 0.2 x 0.2 for 1771 more than 2.5. The pads are arranged to provide a semi-pointing geometry with respect to the ATLAS interaction point. Further details of the design of the HEC have been published elsewhere2. 2. Status of Module Production and Assembly Tooling The construction of the Hadronic Endcap Calorimeter is well under way. At the time of the conference (by end of March 2002) 77% of all modules had been built world-wide and 63% of the final number of modules had been cold tested. Beam tests have been completed, with a total of 24 production modules having been exposed to beams of electrons, pions and muons. At the same time the wheel assembly table and rotator have been completed and put into operation. Assembly of the first HEC wheel will commence during the summer of 2002.
3. Beam Tests 3.1. Setup
The beam test cryostat provides enough space to hold a set of 3 front modules and 3 rear modules. Production modules were tested during 6 beam periods of 2 to 3 weeks each. For the tests, the modules are arranged such that they
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are “standing” on the outer circumference of the wheel (see Fig. 2). Beam tests have be performed with electrons in the energy range of 6 GeV to 193 GeV, pions in the range of 10 GeV to 200 GeV and muons of 120 GeV, 150 GeV and 180 GeV. The horizontal movemeilt of the cryostat and vertical steering of the beam allow the testing of a number of different readout channels and detailed position scans of the modules. Fifteen well defined “impact points” (see Fig. 2) are used to compare the response of different modules and different beam periods.
Figure 2. Three modules in a typical beam test setup. The diagram illustrates the accessible impact points for the beam (A to 0 ) .
Longitudinally, the LAr gaps are grouped into 4 readout-channel segments. The first longitudinal segment (LSEG) comprises 8 LAr gaps of the front wheel, while the second LSEG comprises 16 gaps. The rear wheel is divided into two longitudinal segments of 8 LAr gaps each.
3.2. Module Performance Signals are recorded typically in 16 or 32 time samples, separated by 25 ns each. The amplitude is determined with optimal filtering3 over the 5 time samples in the region of the signal peak. Pedestals are obtained from the 5 signal free time samples preceeding the signal. After subtraction of the electronic noise in quadrature, the energy resolution can be parametrized as
where @ denotes a quadratic sum.
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e0 :, Least square fits t o the data recorded with electron beams and averaged over several impact points yield the following results:
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The uniformity and linearity of the calorimeter can be demonstrated by the response to electrons measured at various impact points and the average
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Figure 7 shows the amplitude of the signal in the 4 longitudinal segments as a function of horizontal position for muons of 150 GeV energy. The second longitudinal segment has twice the number of LAr gaps compared to the other 3 segments and therefore contributes a signal that is twice as large as the signal of the other segments. The boundaries between the different modules at x M f 1 7 cm can be detected with the narrow shower of the muon beam.
3.3. Signal Readout
A detailed study of the signal response in the electronic readout chain has been performed for individual ADC channels. The behaviour of distinct parts of the readout chain (preamplifiers, shaper, cables) has been determined separately and was then combined to form an analytical model describing the entire chain5. A comparison between the measured signal shape and the analytical model is shown in Fig. 8. The residual between the two distributions is typically within f l % .
Figure 8. A typical shaped pulse from one readout channel and the residual between the pulse and the analytical model prediction.
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Based on this detailed understanding of the signal pulse, a refined analysis can be performed to determine the dependence of the drift time and the initial ionization current as a function of the electric field applied in the gap. 45
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Figure 9 shows dependence of the drift velocity on the electric field in the LAr gap. Figure 10 shows the initial ionization current as a function of the electric field. Both show good agreement with theoretical expectations.
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The LAr operating temperature of the ATLAS endcap cryostat (87K to 89K) cannot be reached in the beam test cryostat. However, a limited temperature interval can be mapped out, that allows an extrapolation from the testbeam conditions to the operating conditions of ATLAS. Figure 11 shows the dependence of the initial ionization current and the drift time as a function of liquid argon temperature. A linear extrapolation toward ATLAS temperatures indicates that in ATLAS the initial ionization current will be slightly larger while the drift time will be slightly shorter compared to the beam test measurements. 4. Conclusion
The production of modules for the ATLAS Hadronic Endcap Calorimeter is nearly complete. Assembly tooling for the calorimeter wheels is in place and construction 0s scheduled to start in the summer of 2002. Beam tests confirmed that the calorimeter performs as expected. A detailed model of the electronic properties reproduces the data and has proved very useful for the understanding of the detector. References 1. 2. 3. 4. 5.
J. Colas, M.Pripstein, W.A. Wenzel, NIM A294,583 (1990). The ATLAS HEC collaboration, NIM A482,94 (2002). W.E. Cleland and E.G. Stern, NIM A338,467 (1994). W. Walkowiak, NIM A449,288 (2000). Leonid Kurchaninov, private communication.
PERFORMANCE OF THE ATLAS HADRONIC END-CAP CALORIMETER IN BEAM TESTS
A.E. KIRYUNIN* Max-Planck-Institut fur Physik, Werner-Heisenberg-Institut Fohringer Ring 6, 80805 Munchen, Germany (On behalf of the ATLAS Liquid Argon HEC Collaboration)
Serial modules of the ATLAS hadronic end-cap calorimeter have been successfully tested in particle beams at CERN in 2000 and 2001. Main performance parameters of calorimeter modules, obtained by analyses of electron, muon and charged pion data, are presented. Detailed comparisons of experimental results with predictions, based on Geant3 simulations, are done.
1. Introduction The hadronic end-cap (HEC), a copper liquid argon (LAr) detector with parallel plate geometry, is being built now for the future experiment ATLAS at the Large Hadron Collider at CERN. It has four longitudinal layers and covers the pseudorapidity region 1.5 < 1771 < 3.2. In 1998-2001 extensive beam tests of pre-production and serial modules of the HEC were carried out at CERN. Various analyses of large amounts of experimental data and comparisons with predictions, based on Monte Carlo (MC) simulations, allowed to evaluate the performance of the ATLAS hadronic end-cap calorimeter3. This talk summarises the main performance parameters of HEC serial calorimeter modules, obtained in beam tests in 2000 and 2001. A detailed description of the test-beam setup and discussion of the physical program of module tests are presented in Reference2. The talk is organised as follows. In Section 2 the description of the simulation package and simulation procedures, used for data analyses, are presented. In Sections 3 and 4 the main results of electron and muon studies are given. Section 5 is devoted to analyses of pion data. *On leave of absence from Institute for High Energy Physics, Protvino, Russia
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2. Monte Carlo Simulations for HEC B e a m Tests
The evaluation of the HEC performance requires the comparison of experimental data, obtained at beam tests, with detailed Monte Carlo simulations. To fulfill this task a special software package has been prepared4. It is based on Geant35 (version 3.21), a toolkit for the simulation of particle passage through matter. The package allows to simulate the response of the HEC modules to various particle beams of different energies. The geometry of the test-beam setup is described there in full detail. For example, the HEC module description includes not only copper plates and gaps of LAr, but also polyimide electrodes, copper pads and tie-rods. All elements of the beam-line, such as the cryostat, multi-wire proportional chambers and scintillating counters, extended over a distance of 30 meters, are included as well. The GCALOR code for the hadronic shower development is used for main part of simulations. To estimate the influence of the energy leakage (due to the limited acceptance of HEC modules) on the performance of the calorimeter, “virtual” leakage detectors are implemented in the simulation framework. In this leakage detectors the kinetic energy is summed up for all particles leaving the HEC modules through lateral and back sides. 3. Analysis of Electron Data
Energy scans in the range 6 GeV < EBEAM< 193.1 GeV have been performed for electrons at 15 different impact points covering the area accessible through the beam window of the cryostat. To reconstruct the energy, clusters of cells have been defined. The cluster size has been kept fixed for each impact point so that the noise contribution can be better studied and controlled. Read-out channels near each impact point were included if they had an average signal of more than 200 nA at 175 GeV. This selection yields a typical cluster size of 6 read-out channels. Simulation studies give an estimated energy leakage of only 0.5 % outside selected clusters. To estimate the electronic noise contribution, the noise from the cluster channels has been summed. Thus any correlation between different channels or any coherent part in the noise is automatically taken into account. The equivalent noise amounts to 0.6 GeV for electron clusters. N
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3.1. Energy Response and Resolution
For the energy reconstruction a single parameter C Y E M ,connecting the measured current and the nominal beam energy, has been used. In Figure l the relative response is shown as a function of the beam energy for four different
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Figure 2. The sampling term (top plot) and the constant term (bottom plot) of the energy resolution for electrons at different impact points (results of the September 2001 run period).
impact points. The data demonstrate good linearity (mostly 310.5 %) and are in agreement with Monte Carlo predictions. Variation of the scale factor Q E M from point t o point is also within 1 % (which shows the good homogeneity of HEC modules). Another important calorimeter characteristic is the energy resolution. For the direct comparison of the resolution at different impact points and with Geant3 predictions, the electronic noise contributions were subtracted in quadrature from the experimental resolution. The energy dependence of the resolution can be parameterized by the following two term formula:
with a sampling term A and a constant term B . In Figure 2 experimental and predicted values of the sampling and constant terms at different impact points are presented. It can be seen, that corresponding values are very close. In average, the energy resolution for electrons is characterized by the sampling term A = 21.5 f 0.2 %GeV1/2 and the constant term B = 0.1 f 0.2 %.
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3.2. Ionization Current and Visible Energy
One of the important parameters, obtained during analyses of test-beam data, is the conversion factor between the visible energy deposited in LAr and the measured ionization current. This factor can be obtained by the direct comparison of the reconstructed signal in one channel and the amount of visible energy in the same channel, as predicted by simulations. Electron energy scans at eight different impact points were used for this study. Signals in the most loaded channels were compared. In total 149 experimental runs, taken in 2000 and 2001, were used for this analysis. In Figure 3 the distribution of the ratio between the measured current in one channel and the visible energy in this channel, obtained from simulations, is shown. The mean value of the distribution is 7.188 nA/MeV, its r.m.s. is 0.074 nA/MeV. -1%
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The theoretical value of such a conversion factor can be calculated according to the following formula, based on the Thomas-Imel model6:
where q is the electron charge, ~,=23.2 eV/pair the ionization energy per electron-ion pair, ~d,.=450ns the drift time, E0=0.84 kV/cm a model param-
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eter, E the electric field in LAr and FH = 0.973 the correction for the volume of honeycomb spacing mats (which were not included in simulations). The theoretical value has some uncertainties (the drift time is not exactly known for each impact point, for example). Decreasing cuts in Geant3 can lead to a certain increase of the simulated visible energy. The overall estimate of uncertainties due to known factors is at the level of f l %. As it can be seen from Figure 3 the values of conversion factor, obtained by analysis of HEC test-beam data and by theoretical calculations, are in good agreement. 4. Analysis of Muon Data The muon data are very useful because of the following reasons. At first, they allow to study peculiarities of the reconstruction of low energy signals in HEC modules. At second, horizontal and vertical scans test the homogeneity of the calorimeter at full depth. Muon beams of 120, 150 and 180 GeV have been used in HEC beam tests. The main results of muon analyses are the following: - Signal-to-Noise ratio (obtained for a four channel cluster) is 5.4 (5.9) for 120 GeV (180 GeV) muons. So, muon signals are clearly seen in the HEC. - Electron-to-Muon ratio (when most probable values of muon signals are used) equals to 0.93f0.02 (0.92f0.02) for muons at 150 GeV (180 GeV). - Electron-to-MIP (minimum ionizing particle) ratio equals to 0.99f0.02. Errors presented here are pure statistical. The systematic error has been estimated using the maximum and minimum values obtained using different calibration runs or data at different impact points and varying the analysis cuts used. From these studies an estimate of the systematic error of the Electronto-Muon and Electron-to-MIP ratios is f0.03. The agreement between the data and the simulation is within errors. 5. Analysis of Charged Pion Data
Energy scans in the range 10 GeV < EBEAM< 200 GeV have been performed for charged pions at the standard impact points. Energy reconstruction was done within clusters of fixed size at each point. Channels with an average signal of more than 15 nA at 180 GeV beam have been used. The typical cluster size for the pion reconstruction is 50-60 read-out channels. The electronic noise contribution in such clusters is at the level of -6 GeV. Simulation studies give an estimated energy leakage of 4.5-5.5 %. This value consists of 1-2 % leakage outside selected clusters within calorimeter modules and 3.5 % leakage through their lateral and back sides (as “measured” in the leakage detectors).
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5.1. Energy Resolution In Figure 4 the sampling and constant terms, obtained by fits with Equation 1 at different impact points, are presented. Results are in agreement. The average values are A = 70.6f 1.5 %GeV1/' and B = 5.83~0.2%. It can be seen that Geant3 gives a somewhat too optimistic energy resolution in comparison to the experiment. The obtained values of the resolution are affected by the energy leakage. Special studies7, based on the analysis of simulated samples, allowed to derive the HEC intrinsic energy resolution. For the sampling term A = 62.2 f 1.8 %GeV1/2 and for the constant term B = 5.2 & 0.2 % have been found typically.
5 . 2 . Ratio e / h An important intrinsic characteristic of a calorimeter is the ratio of the electron to hadron response elh. The deviation of this ratio from 1, typical for a noncompensating calorimeter, leads to a worsening of the energy resolution and
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Figure 4. T h e sampling term (top plot) and the constant term (bottom plot) of the energy resolution for pions at different impact points.
Figure 5. T h e energy dependence of the e/n-ratio for uncorrected data (top plot) and after correcting for energy leakage (bottom plot). T h e lines give fits with Equations 2.
gives rise to a constant term of the energy resolution. The elh-ratio and the
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measured e/n-ratio are related by the following equations8:
here fir. is the mean fraction of the initial pion energy deposited via electromagnetic cascades. For pions typical values are E(, M 1 GeV and m M 0.85. The measured eln-ratio for one of the impact points is shown in Figure 5 (top plot) as well as the result of the fit using Equations 2. These results are biased due to the energy leakage outside the chosen cluster and the given calorimeter acceptance. Correction factors were extracted from simulated samples and applied to experimental data. In the bottom plot of Figure 5 the corrected dependence of the elr-ratio on the beam energy is presented. The applied correction considerably improves the quality of the fit. Estimates of the systematic errors were done taking into account the precision of the leakage correction and the variation of the e/h-ratio from point to point. The final result for the HEC is e l h = 1.4950.01f O . l O , where systematic errors dominate. The prediction of the Geant3 package (with GCALOR) is e l h = 1.32
5.3. Longitudinal and Transversal Shower Profiles
The HEC has four longitudinal layers. Studying the energy depositions in those allows to evaluate the longitudinal development of hadronic showers. Figure 6 shows the energy dependence of the mean energy fraction (normalized to the total energy in a cluster) deposited in the individual longitudinal layers of the HEC module. The energy fraction in the last part is increasing noticeably with the beam energy. Comparison of experimental results with predictions of the Geant3 package shows reasonably good agreement. The HEC granularity itself is not fine enough to see details of the transversal shower shape. But they can be studied somehow using the horizontal scan data obtained with pions at 200 GeV. The signals in the vertical (77) channels related to a given horizontal (4) read-out channel have been summed to towers. In Figure 7 the signal in one of the &towers as a function of the x-coordinate of the impact point is shown for the four longitudinal layers. The increase of the hadronic shower size width with the longitudinal propagation of the hadronic shower is clearly visible. The Geant3-based simulation (with GCALOR as a hadronic shower code) gives a good description of the data, except for the extreme tails where Geant3 predicts a slightly larger shower size than observed in the data.
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Figure 6. The mean energy fraction deposited in the four longitudinal layers as a function of the beam energy.
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Figure 7. Transversal shower shape: the mean energy fraction in a 4 tower (ztower in scan, centre at -25.5 cm) in dependence on the 2-coordinate of the beam impact position in the the four longitudinal layers.
6. Acknowledgements
I would like to thank all my colleagues from the ATLAS Liquid Argon HEC collaboration for their work on building and testing HEC calorimeter modules and analysing test-beam data. References 1. ATLAS Collaboration, “Liquid Argon Calorimeter Technical Design Report”, CERN/LHCC/96-41 (1996). 2. Talk by M. Fincke-Keeler at the “Ionization calorimetry” session of this conference. 3. ATLAS Liquid Argon HEC Collaboration, Nucl. Instr. and Meth. A482, 94-124 (2002). 4. A.E. Kiryunin and D. SalihagiC, “Monte Car10 for the HEC Prototype: Software and Examples of Analysis”, Internal ATLAS HEC Note-063 (1998). 5. R. Brun et al., “GEANTS”, CERN DD/EE/84-1 (1986). 6. J. Thomas and D.A. Imel, Phys. Rev. A36 N.2, 614 (1987). 7. A.A. Minaenko, “Analysis of Test-Beam Data, Obtained with Module Zero of Hadron End-cap Calorimeter”, Internal ATLAS Note LARG-99-011 (1999). 8. R. Wigmans, Nucl. Instr. and Meth. A265, 273 (1988).
A HIGH RESOLUTION LUMINOSITY MONITOR FOR SLAC EXPERIMENT El58
G . M. JONES Stanford Linear Accelerator Center, 2575 Sand Hill Road, Menlo Park C A 94025 E-mail: markjOslac.stanford.edu (For the E l 5 8 Collaboration)
A calorimetric detector based on ionization has been employed as a low-angle luminosity monitor for the parity violation experiment E15S1 at SLAC. The experiment utilizes a 50 GeV polarized electron beam on a liquid hydrogen target. The detector looks at high energy Mott and Moller scattered electrons, with a per pulse flux of 4 x los particles. This large signal allows the device to serve the dual role of monitoring target density fluctuations, as well as detecting false asymmetries. In the first physics run of the experiment, the detector has achieved a per-pulse intensity asymmetry resolution of 170 parts per million. The linearity of the device also has been verified to 51%.
1. El58 Overview 1. l . Physics Goals The electroweak theory has been probed to an astounding level at the Zo resonance through the joint contributions of LEP and SLC. The purpose of El58 is to complement these results by measuring the weak mixing angle at a much lower Q 2 . This will allow new insight into the running of sin20w and form a more complete test of the Standard Model. Figure 1is an adaptation of a plot by Czarnecki and Marciano2 displaying the Standard Model prediction for the running of sin20w. Here, uN refers to the NuTeV experiment at Fermilab3, and APV denotes the result of the atomic parity violation experiment on cesium conducted at the University of Colorado at Boulder4. The NuTeV result is actually 3a above the Standard Model. Since the publication of the Boulder experiment, the interpretation of their result has evolved as new theoretical treatments have been applied576t7i8. In the plot, the APV point is now roughly 2a below the theoretical valueg.
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Figure 1. Standard Model running of sin'tlw
1.2. E l 5 8 Layout The experiment utilizes a longitudinally polarized electron beam provided by the 50 GeV linac at SLAC on an unpolarized target of liquid hydrogen (LHZ) to measure the parity-violating asymmetry in Moller scattering. Following the target, a dipole chicane and a quadrupole package are used to focus the Moller electron signal onto the main detector. This setup is depicted in Figure 2. From Standard Model calculations', the expected asymmetry for El58 is -150 parts per billion (ppb). Due to the small size of this number, it is extremely important that all sources of false asymmetries be understood and quantified.
+ Beam 48 GeV Lmac
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Figure 2.
1.3. Purpose of Luminosity Monitor
The luminosity monitor (lumi) is located 70 meters downstream of the hydrogen target at an angle of approximately 1 milliradian. From GEANT simulations of a nominal beam rate of 5 x 10l1 e- per pulse, the lumi is expected to see a flux of 4 x lo8 e-. Based purely on counting statistics, this extremely high counting rate sets the scale for the maximum resolution of the detector at the 50 ppm level. Simulations done at SLAC" show that the signal of the lumi is comprised of 70% Mott scattered electrons, with the remaining 30% made up of high
730
energy Moller electrons. The average energy of these electrons is -40 GeV. In this kinematics region, the theoretical physics asymmetry is only 5 ppb. This is the defining feature of the lumi: it should measure no asymmetry within the proposed statistics of the experiment. This would be a powerful test against the presence of false asymmetries. 2. Detector Design
2.1. Concerns and Constmints
The ultimate design of the lumi was dictated by the strict requirements of E158. The main concern was in keeping the intensity asymmetry resolution at the scale of 100 ppm. For E158, custom 16-bit adcs were constructed on site with noise properties sufficient for the experiment. Minimizing systematics due to non-linearities was also a concern. Over the full course of the experiment, the charge asymmetry is expected t o be at the level of 200 ppb or below. Because of the small size of the Moller asymmetry, it is desirable to keep any individual systematic effect at the 1 ppb level. This translates to a demand on linearity at the 0.5% level. An interesting requirement on lumi design occurs because of asymmetries found in synchrotron radiation, due to a possible presence of transverse polarization of the electron beam. From simulations, it is known that about 17W of synchrotron radiation hits the lumi, originating mainly from the final dipole magnet of the spectrometer. This is a non-negligible portion of the 150W total signal. Inserting El58 spectrometer parameters into the theoretical formulas", and assuming a transverse beam polarization of 1%nets the conclusion that the contribution to the total detector signal must be less that 1%in order to keep the observed asymmetry on the few ppb level. The final requirement on the detector design was that it had to be robust against radiation damage. Over the course of the experiment, the detector will get a dose on the order of a gigarad. 2.2. Physical Construction The lumi is comprised of 16 individual chambers, arranged into two separate, complementary detectors. These are simply called the "front" and "back" lumi. The front lumi serves as the primary device, while the back lumi is used mainly as a cross-check. Upstream of the front lumi is 7 radiation lengths of aluminum, which performs the dual role of showering the signal and attenuating the synchrotron radiation background. Between the front and back lumi detectors is an additional 4 radiation lengths of aluminum. Figure 3 depicts the full detector layout.
731 Side View Chamber5
Aluninurn
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Figure 3.
Inside of each chamber, there are 11 parallel plates, positioned transverse to the beamline. These are alternately kept at lOOV and ground, so that when a charged particle traverses the chambers, the electrons it liberates through ionization are collected. A signal is actually read out from each plate in the device, since they are all capacitively coupled. By reading in the signals differentially, noise pickup from the cables is reduced. The separation between the plates is approximately one millimeter. This small distance was chosen to ameliorate possible non-linearities induced by unwanted recombination of liberated electrons and ions in transit to the plates. The buffer gas was chosen to be nitrogen, since it provided adequate signal sizes and did not require the,special attention required by a flammable gas. Simulations in EGS show that the front degrader produces a x40 amplification of the incident signal. The lcm of nitrogen gas in each chamber also produces a similar amplification factor. The signal sizes seen from a single front chamber for typical running conditions are between 4 to 8 volts. This allows the detector to be run entirely without amplifiers. The ratio of the observed signals in the front to the back lumi is about 3:1, which agrees with the simulations. Since the back chamber has a much reduced signal, it can serve as a linearity check on the front ring of chambers. The fact that the front and back rings of the detector measure the same signal flux allows the back chambers to be a crosscheck for the front chambers for the measured asymmetries as well. 3. Detector Performance 3.1. Resolution
The ultimate per-pulse intensity asymmetry resolution achieved during the first run of El58 was at the level of 170 ppm for the front ring of the detector, and 250 ppm for the back ring. To achieve this level of resolution, it was necessary to remove beam related
732
effects from the detector signal. This is accomplished by finding the slope of the correlation between asymmetries in the detector and a beam position monitor (bpm) and then subtracting out this relation. After implementing these corrections, the detector becomes less sensitive to beam parameters and approaches its maximum possible resolution. For E158, seven individual bpms are used to remove the dependence on x and y position and angle on target, as well as energy related effects. Before this regression procedure is done, it is common for the raw resolution of the front detector to be at the 250 ppm level, while the back was often near 425 ppm. By noting the sensitivity of the detector to fluctuations in these beam parameters, and the corresponding resolution on that parameter provided by the bpms, the predicted final regressed resolution of the detector can be calculated. In this way, all sources of noise for the detector can be itemized. It should be noted that the bpms for El58 attained an excellent position resolution, at the level of 2 microns. Taking into account the noise contributions from bpm and toroid resolution, as well as including counting statistics and pedestal fluctuations, it is found that the resolution of the detector should be 110 ppm. This is significantly below the observed 170 ppm, pointing to an unknown noise source around the level of 100 ppm. The source of this extra noise contribution is still unidentified, though a likely candidate is electronics crosstalk. It has been observed that the resolution of the detector is greatly affected by adjusting timing parameters on the adcs. The 170 ppm resolution is only achieved for a very specific timing setting. For most other settings, the resolution worsens to 280 ppm. Research into the implications of this is still ongoing.
3.2. Linearity Conceptually, the linearity of a detector is a simple parameter. In practice, however, determining the linearity of the luminosity monitor to the level of 0.5% has proven to be quite a challenge. Though several methods have been employed, the most promising technique involves making cuts on beam parameters below bpm resolution and then plotting lumi asymmetry (not normalized by toroid) vs. toroid asymmetry. By making tight cuts, and working with asymmetries, the large effects coming from beam motion are mitigated. About 0.1% of the data survives this cut. The deviation of the observed slope from unity is then a direct measure of the linearity of the lumi-toroid system. Figure 4a shows the slopes obtained from this method for each chamber in the front ring of the lumi. Clearly, there is still a systematic effect related
733 u a
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1GeV). The size of these preclusters is limited to 2Rcone x 2R,,,, in the r] - 4 plane, where r] and 4 denote the pseudorapidity and the azimuthal angle and R,,,, is the parameter of the jet algorithm which controls the size of the jets. After that for each precluster a cone is defined by all seed towers inside the precluster and all towers with AR = ~ ( A V (A4 ) ~ )2 < R,,,, with respect to the highest ET tower. The centroids of the cones are calculated. The identification of the members of the cones and the calculation of their centroids is repeated until the old centroids (the cone axes) agree with the new ones. Note that every seed tower of a precluster is kept in its cone even if the angular distance to the cone center exceeds Rconedue to the migration of the centroid during the iteration. This (unusual) prescription is called “ratcheting” and is unique to the JetClu algorithm. In the last step overlapping stable cones have to be treated because each calorimeter tower may only belong to one jet. In the JetClu algorithm a pair of overlapping cones is merged if more than 75% of the transverse energy of one of the cones is shared by the other one. Otherwise they are separated using an iterative algorithm. The towers are redistributed to the cone whose centroid is closer, and the centroids are recalculated until a stable configuration is reached. The JetClu algorithm is neither infrared safe nor collinear safe. Moreover the cone iteration process uses ratcheting, which is difficult to simulate in perturbative calculations.
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2.2. Midpoint
The Midpoint algorithm has a substantially reduced infrared and collinear sensitivity compared to cone algorithms used in Run I. This was achieved by adding seed locations for trial cones between pairs of stable seed-based cones. The algorithm works as follows: 0
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Iterate cones starting at each seed tower (no preclustering). No ratcheting is done in the iteration process. For each pair of stable cones whose centers pi and p j lie within an angular distance A R < 2 . R,,,,, iterate a cone starting at the midpoint pi i-p j .
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Split or merge overlapping cones. Cones are merged if they share at least 50 % of the transverse energy of the less energetic cone.
2.3. KtClus Both CDF and DO will employ ICT clustering algorithms3 in analyses of Run I1 data. Their advantage is that by design they are infrared and collinear safe and can be applied in the same manner to calorimeter towers, hadrons and in perturbative calculations.
3. Comparison of cone algorithms
In this section the dependence of physical observables on the choice of the jet algorithm is discussed to get an understanding of the differences between the jet algorithms presented in Section 2. To this end representative jet algorithms are applied to a data set that was generated with the HERWIG 6.1 Monte Carlo program and then run through the CDF detector simulation. It consists of 100,000 QCD 2 + 2 parton reactions inside pp collisions at a center-of-mass energy f i = 2 TeV. The two primary outgoing partons are required to have a minimum p~ of p ~ , =~100 i GeV. ~ The jet algorithms used are the JetClu and the Midpoint algorithm with a cone size R,,,, = 0.7.
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Figure 1. The difference in ET between matched pairs of JetClu and Midpoint jets. The left hand plot shows the AET distribution for leading jets, the right hand plot shows the mean values ( A E T ) as a function of E p C 1 u .The distributions plotted in grey were calculated using JetClu in its original version, while the black histograms were calculated using JetClu with the ratcheting switched off.
In the shaded histogram of the left hand plot in Figure 1 the difference
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of the transverse energy ET of the leading JetClu jet and the corresponding Midpoint jet is plotted. The matching of the jet pair requires their angular separation t o meet A R < 0.1. The distribution exhibits a peak at AET = 0 for which the leading JetClu and Midpoint jets are identical. However, a bias towards positive AE, values is also clearly visible. On average, leading JetClu jets have about 1GeV higher ET values than leading Midpoint jets. A similar conclusion can be drawn from the distribution plotted in grey in the right hand histogram in Figure 1. Here the mean difference ( E p c * "EFidPoint) for matched jet pairs is plotted as a function of EPC1". The observed differences are due t o the ratcheting which is used in the iteration process of the JetClu algorithm only. Since calorimeter towers belonging t o the preclusters never leave the cones during the iteration process, the use 0 of ratcheting can lead to stable cones, and hence to jets, which exceed the cone size R,,,,. Switching off the ratcheting in JetClu leads to a much better agreement between the transverse energies not only of matched leading JetClu and Midpoint jets, Figure 2. Event display pictures of a simulated QCD event but also over the whole in the C D F calorimeter. The upper picture shows the jet ET range covered by the configuration as reconstructed with the JetClu algorithm, the lower picture shows the one obtained with the Midpoint data set (black distribu- algorithm (R,,,, = 0.7). T h e black (seed) towers in the tions in Figure 1). lower picture are not included in any jet. Since ratcheting is difficult to simulate in perturbation theory, it has not been implemented in the Midpoint algorithm. However, it ensures that all seed towers in an event are included in stable cones and hence in jets. Figure 2 shows an event in which the lack of ratcheting in the Midpoint algorithm leads to a substantial
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part of the transverse energy not included in any jet. Cones which are initiated by the seed towers at (77 NN -0.2, $ NN 100') invariably migrate towards the nearby more energetic towers, which in the end form the leading Midpoint jet. The black towers remain unclustered. In the JetClu case these seed towers are not released from the cone and in the end are part of the leading jet. 4. Improving the Midpoint algorithm
To provide insight into the issues raised by Figure 2 a simple, but informative analytic picture will be discussed4. It describes the dynamics of cones under the influence of partons in the iteration process and will serve to illustrate the impact of showering and hadronization on the operation of cone jet algorithms. Consider a distribution of partons with (transverse) energy
(For simplicity, the 4 coordinate is suppressed in this 1-dimensional model.) The total energy contained in a cone C whose center is placed at 77 is given by: i
i€C
Since in the iteration process a cone moves under the influence of forces which are created by the partons and which are linear functions of the parton energies and their distances to the cone axis, a potential can be assigned to a cone with its center at 77: 1 ET,i . ((77 - yi)2 - R 2 ) const. Vc(7)= - . (3)
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Stable cones can be found in the minima of Vc(q) and can be calculated by requiring the force FC (77) to vanish:
For a scenario involving two partons of (scaled) energies E T , ~= 1 and E T , ~= 0.7 at 711 = 0 and 772 = 1.0 the functions defined in Eqs. 1-4 are plotted in Figure 3 (bold solid lines). The potential V C ( ~ )exhibits three minima corresponding to the expected positions of the stable cones found by the Snowmass and the Midpoint cone algorithms (R,,,, = 0.7). Since both partons are entirely within the center cone, the overlap fractions are unity, and the usual splitting/merging routine will lead to a single jet containing all of the initial energy. In fact, an additional parameter Rsep is included in the NLO calculations5 such that stable cones containing two partons are not allowed for
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angular separations AR > Gep.Rcone.Its value was chosen to be &ep = 1.3 to yield reasonable agreement with the Tevatron Run I data. The specific parton configuration in Figure 3 will thus yield two jets in the theoretical calculation, while the Midpoint algorithm will produce only one jet.
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Figure 3. A study of the “cone dynamics” in the Midpoint algorithm (R,,,, = 0.7). The four plots show the quantities defined in Eqs. 1-4. The different line styles correspond to different values of the smearing parameter Q. In addition, the dotted lines denote the case u = 0.25 and R,,,, M 0.495. The Vc(9)curves are shifted by (unphysical) constants for better readability.
A major difference between the perturbative and the experimental level is the smearing that results from perturbative showering, non-perturbative hadronization and detector effects. These effects are simulated in the model using gaussian smearing. After replacing the delta functions in Eq. 1 with gaussians of width (T = 0.10, the middle minimum of Vc(v) and thus the
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middle stable cone has been washed out (thin solid lines in Figure 3) resulting in a two jet configuration. However, no energy is missed by the Midpoint algorithm in the case (T = 0.10. Only with increased smearing, e. g. by setting (T = 0.25, a value which is supported by jet shape measurements, also the second stable cone, corresponding to the second parton, has been washed out (dashed lines in Figure 3). This explains why the Midpoint algorithm fails to include the energetic towers shaded in black in the lower picture of Figure 2 into the neighboring or separate jets. The iteration of any cone containing these towers invariably migrates to the nearby higher ET towers. This behavior can be avoided by diminishing the influence of the energy at the edge of the cones. The simplest fix is to use two values for the cone radius R,,,,, one during the search for the stable cones and the second during the calculation of the jet properties. As an example, a reduced search cone radius of R,,,,/t/Z x 0.495 is used in the dotted lines in Figure 3. The Vc(q)curve indicates that both outer stable cones at the positions of the smeared partons are found leading to a two jet configuration, in agreement with the result of the Snowmass algorithm with Rsep= 1.3. To understand more deeply the behavior of the JetClu algorithm, a similar analysis can be carried out after modifying Eqs. 2-4 to take the ratcheting into account. This analysis suggests that two different stable cones are found, independent of the amount of smearing. The first stable cone is at the position of the more energetic parton, while the second one can be found at the less energetic parton in case of little smearing and in the middle position in case of (T = 0.25. In the latter case the two stable cones will be merged into one jet, as observed in the upper picture of Figure 2. The result of this analysis is that the Midpoint algorithm (and any other cone algorithm based on the Snowmass accord without ratcheting) , applied to experimental data, can fail to reconstruct entire partons if there is a more energetic parton within a distance R,,,, < d < 2.R,,,,. This deficiency can be eliminated by modifying the prescription of the Midpoint algorithm presented in Section 2.2 as follows: 0
0
In the cone iteration process reduce the cone radius, e. g. by a factor of 1/&. After reaching a set of stable cones, recalculate their contents using the nominal cone size R,,,,. Then go to the splitting/merging process.
Figure 4 indicates that the suggested fix indeed improves the behavior of the Midpoint algorithm in the case of Monte Carlo events which were run through
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the CDF detector simulation. It contains the distributions of the difference of the total transverse energy contained in JetClu jets and in jets reconstructed with the Midpoint (shaded histogram) and the fixed Midpoint algorithm (solid line) respectively. The JetClu algorithm was chosen as a reference because by design it includes all seed towers (ET > 1GeV) in jets. Entries in the tail of the shaded histogram are caused by events in which ; f
the Midpoint algorithm fails to include a large fraction of the transverse energy in the event in jets. The suggested fix is able to reduce the tail considerably by recovering the stable cones missed in the original Midpoint algorithm due to the influence of nearby more energetic clusters of calorimeter towers. Moreover it slightly shifts the whole distribution to the left because of an increased efficiency in finding low ET jets.
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Figure 4. The difference of the total transverse energy contained in JetClu and in Midpoint jets (Rcone = 0.7). The shaded histogram shows the distribution for the original Midpoint algorithm, the solid line histogram shows the one for the fixed Midpoint algorithm with R,,,, % 0.495 in the iteration process. Only jets with ET > GeV were 'Onsidered for the calculation of the total E T . Y
5. Summary and Outlook
As suggested in the R~~ 11 workshopl CDF and D0 are working On the development of common tools for the reconstruction of jets, which will be employed in the analyses of data that both detectors are actively taking. References
1. G. C. Blazey et al., Run 11J e t Physics: Proceedings of the Run 11QCD a n d Weak Boson Physics Workshop, FERMILAB-Conf-00/092-E (May 2000). 2. J. E. Huth et al., in: Research Directions for the Decade: Snowmass 1990, July 1990, edited by E. L. Berger (World Scientific, Singapore, 1992), p. 134. 3. S. D. Ellis and D. E. Soper, Phys. Rev. D48, 3160 (1993); S. Catani, Yu. L. Dokshitzer and B. R. Webber, Phys. Lett. B285, 291 (1992); S. Catani, Yu. L. Dokshitzer, M. H. Seymour and B. R. Webber, Nucl. Phys. B406, 187 (1993). 4. S. D. Ellis, J. Huston and M. Tonnesmann, On Building Better Cone J e t Algorithms, hep-ph/0111434. 5. S. D. Ellis, Z. Kunszt and D. Soper, Phys. Rev. Lett. 69, 3615 (1992); S. D. Ellis, in: Proceedings of the 28th Rencontres de Moriond: QCD and High Energy Hadronic Interactions, March 1993, p. 235; B. Abbott, et al., FERMILAB-Pub97/242-E (September 1997).
SUPPRESSION OF PILE-UP NOISE IN A J E T CONE
ALEXANDRE SAVINE University of Arizona E-mail: savin~physics.arizona.edu Multiple low-pT (min-bias) interactions within a beam crossing at a high luminosity hadronic collider contribute to pile-up noise in the calorimetric measurements of jets. I show how to minimize this noise by taking advantage of correlations in these background events. Substantial reductions are possible
A cross-section for inelastic p p interactions (including diffractive) at LHC energies is estimated as 80mb. During high luminosity operation ( L = 1034cm-2s-1)there will be 20 low - p in ~ every beam crossing. Those interactions create a substantial fluctuating background in the detector subsystems, including calorimeters. Since the beam crossing are separated by only 25ns, min-bias signal from previous crossings also contributes to this background, depending on the signal shaping and data processing algorithms. As any noise does, the pile-up background affects the energy resolution and forces to increase p~ thresholds in the calorimeter. Present research was aimed on reduction of this negative impact. There are few sources of the pile-up fluctuations: (1) Variation of the beam crossing conditions like amount of protons in each bunch, beams relative alignment and focusing variations. (2) Poisson fluctuations of interactions number (crossing to crossing). (3) Physics of each individual proton-proton interaction. (4) Shower development:
(a) Interactions in the beam pipe elements, tracker, calorimeter support/cryostat (b) Shower development in the calorimetric system itself (c) Albedo of the calorimeters
First two factors on this list determine number of interactions and are same for every calorimeter cell. Fluctuations introduced by variation of interactions number behave exactly like a coherent noise, while fluctuations coming from individual interactions are responsible for a stochastic noise. Indeed, low - p~
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events are independent, but are randomized by same QCD rules. Figure 1 shows three events with different number of interactions. There are numerous peaks from individual showers, but it is also clear that they rest on top of a well-defined 'table', proportional to the number of interactions.
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Correlations between the visible energies in the jet cone at q = 0.9 and q-slice at
For large groups of cells (like jet cone) coherent component of the pile-up increases in proportion with number of cell, while the 'stochastic' component is proportional to square root of this number. Figure 2 demonstrates such a combination of coherent and uncorrelated fluctuations. It also provides a clue for the pile-up reduction algorithm: the calorimeter shall be used an instant
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'luminosity monitor'. Of course, the regions of interest with their large signal shall be excluded from this the analysis. N=32
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Figure 3. Scheme of the Dynamic Pileup Suppression: C, and CfoT' are raw and corrected cone sums, Aj is an average 0.2 x 0.2 tower response at q j . w i j is a set of coefficients minimizing the pile-up RMS in the cone while keeping average at zero.
Figure 3 shows how the optimal weights were determined for pile-up noise reduction. lOOk Lou, - - p ~interactions were generated by PYTHIA 6.136. Simplified detector (beam pipe and bulk lead calorimeter) was used to run GEANT 3.2111. Segmentation - Aq x Ad, = 0.1 x 0.1. Interactions were saved one-byone. To simulate min-bias events, random sets of event were chosen. Number of interactions in each event was determined by Poisson random generator. In each generated event several jet cones were taken at different (random) q and d,. Pile-up from previous beam crossings was not included. Used procedure is linear and as a result - luminosity-independent. Despite (some) amplitudes from previous crossings come with negative amplitudes, they do not break the linearity of described procedure. Compareson of pile-up spectrum before and after suppression is presented at Figure 4. As was expected, pile-up suppression algorithm reduces the Pois> 7GeV (and son assimetry of the spectrum. Rate for events with E$" EFrS < -7GeV) is reduced by 213, rate above 20GeV - by 314. This region is marked at the semi-log plot as 'True Pileup'. At the same time, even the min-bias events may deliver some well-collimated jets. They contribute to the high energy tail: there is no improvement at E$IS > 50GeV. Indeed, this is
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In addition to the RMS and peak width reduction, Dynamic Pile-up Supression improves the shape of the pile-up noise. Though still not a perfect Gaussian, corrected spectrum is more symmetric. Choice of the Jet Cone size for measurements at the high luminosity is also affected by a pile-up noise. Though it is commonly recognized that A R = 0.7 is much better from the acceptance point of view, much smaller A R = 0.5 is considered maximum acceptable when accelerator is running at L = 1 0 3 4 ~ - 2s- 1 What can the Dynamic Pile-up Supression do here? Since this method is aimed on the coherent component of the pile-up, it works better for larger cones. Indeed, it turns out that (Figure 5) the Dynamic Supression reduces the pile-up in the AR = 0.7 Cone down to the A R = 0.5 scale.
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Conclusions (1) Pile-Up noise may be reduced on the event-by-event basis using calorimeter as an instant luminosity monitor. (2) Suppression allows to:
(a) Increase the Jet Cone for better energy measurements (b) Lower the ET threshold for higher efficiensy (Taggin jet in the FCal) (3) Dynamic Supression requires very small volume of data:
(a) 50 digitized sums (Aq = 0.2 rings) (b) 50 integer tower counts (to exclude region of interest)
(4) Described procedure is independent of any other noise reduction technics
D0’S RECENT RESULTS AND EXPERIENCES WITH THE KT AND CONE JET ALGORITHMS
J. KRANE Iowa State University, Fennilab MS 357, P.O. Box 500, Batavia, IL 60510 E-mail:
[email protected] (For the D 0 Collaboration)
This paper presents recent results, current problems, and possible solutions for analyses that use both the kT and cone jet algorithms. Hadronization of final-state partons can improve the level of agreement between NLO QCD predictions and the inclusive jet cross section observed using k~ jets. The dijet transverse thrust , a jet measurement in two kinematic regions analysis, which also uses k ~ provides where NLO has little predictive power. The results suggest both resummation and higher-order predictions can improve the theory in their respective regions. Finally, the cone jet algorithm, including the recent “midpoint” improvement, contains an inherent weakness, as identified by CDF (see Matthais Toennesmann’s presentation in this session). The D 0 Collaboration is exploring the suggested modification to this algorithm, in the hope that both experiments will use a common algorithm in Run I1 of the Tevatron.
The phenomenology of jets in QCD matured alongside experimental results obtained with the cone jet algorithm. The UA2 experiment used fixed cones of dimensionless size R = 1.3 (in azimuth and pseudorapidity), to compare to leading-order QCD predictions. The large cone size tended to collapse all events into a dijet topology. Years later, the CDF and DO experiments used a version of the cone algorithm (with R = 0.7 and a merge/split function) to compare jet data to NLO predictions. This second generation of jet results enjoyed a factor of two or more improvement in precision. Toward the end of the Tevatron’s Run I, DO implemented a recombinant jet algorithm, the Ellis and Soper’ k~ algorithm, and revisited the inclusive jet cross section measurements previously done with cone. The jet data have been incorporated into the standard parton distribution functions; this article attempts to summarize the open issues facing jet physics today, and how they impact D8’s plans in Run 11. The DO calorimeter2 provides the majority of the jet information for the analyses. The calorimeter is hermetic, consists of more than seven nuclear
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interaction lengths, has fine segmentation (0.1 x 0.1 in q - (6) and covers the pseudorapidity region from -4.2 to 4.2. The active medium is liquid argon, separated by absorbers of spent uranium in most places and isolated regions of copper or steel. DO defines jets with two well-known algorithms. The cone algorithm employs a fixed-radius q - C$contour to select calorimeter cells for energy summation. The energy-weighted center provides a new jet centroid. The jet is redrawn, the contained energy is recomputed, and a new centroid is found, etc. until the jet has stable energy. After this iteration, jets that are very close to one another are either merged or split depending on their fraction of shared energy. The k~ algorithm1 compares the pT-weighted distance of a l o w - p ~ energy cluster to the next largest cluster with a resolution parameter D.If the comparison of clusters i and j ,
is less than p g i / D 2 of the smaller cluster, then the two clusters are combined into a single object with that pT-weighted location. Otherwise, the small cluster is saved to a list of stable jets. The procedure continues until all clusters have been combined or saved. This algorithm exhibits infrared and collinear safety. A sophisticated jet energy scale algorithm3 corrects jet energies for calorimeter response, noise, underlying event, and other effects. By design, the energy scale corrects jet energies back to the “particle level”, such that all detector effects are removed but natural hadronization effects are preserved. D 0 conducted three analyses with the k~ algorithm. First, the multiplicity of subclusters within jets4 revealed a difference between jets of like energy but produced in collisions with different center-of-mass energy. This result implies a difference in the jets from quarks as compared to gluons. The other two analyses are described in the following sections. The last section of this article describes recent work on the cone algorithm. 1. Inclusive Jet Cross Section with ICT
The information from this analysis requires accurate and effective statistical comparisons. The DO collaboration takes great care to build a full covariance matrix that appropriately manages the correlations in energy of each individual uncertainty. The availability of the covariance matrix allows DO data to determine the parton distribution functions5@(PDFs) at high-x. Whereas the earlier cone results display clear agreement with available NLO predictions (even before integration into the PDFs), the k~ result (Figure 1) differs from
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the prediction by roughly two sigma. Figure 2 compares cone and kT cross section results to their respective predictions. Because the uncertainties, which largely result from the energy scale correction, are highly-correlated in ET,the normalization differences are not remarkable. Notice instead the shape difference at low ET in the kT cross section; this departure in shape is not consistent with the uncertainties in the data. If the first four data points are ignored, the k~ predictions are consistent with the observed cross section at the 77% probability level (CTEQ4HJ). We conclude that the marginal agreement of the full 24 point comparison results entirely from the effect of the first four points. The actual x2 values (24 degrees of freedom) resulting from a comparison of D0’s inclusive jet cross section with the k~ algorithm and 1771 < 0.5 with NLO QCD predictions from JETRAD appear in Table 1. Table 1. Example of the x2 values. Last row is JETRAD plus a hadronization correction derived with HERWIG.
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A little investigation reveals that the cross section for k~ differs from the cone result because the individual kT jets in each event possess more energy than the matching cone jet. The jet-by-jet energy difference (Figure 3) accounts for the entire difference between the cross sections, as demonstrated by artificially removing the extra energy jet-by-jet. Particle level Monte Carlo simulations7 indicate that the hadronization process scatters some of the original parton energy outside a 0.7 radius cone. The opposite occurs with the kT algorithm, where the found jet contains more energy than the original parton. The shape and general direction of the simulated effect are suggestive, but the magnitude ( k energy ~ - cone energy) is only half the size of that observed in data. Because the jet phenomenology of QCD was largely developed with cone algorithms, it seems possible that unexpected effects unique to the cone aigorithm have been inadvertently incorporated in the PDFs. In that sense, agreement between theory and cone results is not surprising, nor is the marginal agreement between the predictions and the relatively new k~ algorithm’s results. The DO results indicate that a previously ignored missing component in the prediction has now become important. Hadronization effects appear to represent at least some of this missing piece, but in their current form they are not enough to remove the observed discrepancy.
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2. D i e t Transverse Thrust
This analysis employs a novel event shape variable to probe kinematic regions that NLO predictions fail to describe. DO defines the dijet transverse thrust as
where the summation of transverse momentum, projected onto vector ii, occurs over i jets, with ii selected such that TT takes its maximum value. To avoid distortions caused by calorimeter noise, the summation involves only the two leading jets in the event. In this definition, an event with the leading jets back-to-back in azimuth results in TT = 1.0, and a three-jet final state can take any value in the range 11. With more final states, the minimum angle of the leading two jets can be less than 120 degrees, and even lower values of thrust are possible. Although the observed thrust distribution is well-described by NLO QCD predictions in the range [0.01,0.1], values above and below this range result in large departures of theory from the observed distributions. Figures 4 and 5 display the thrust distributions of two jet samples with different total energya. The right-hand side of the distributions represents the kinematic limits of NLO
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aThis quantity, HT3, characterizes the hardness of the event with the energy sum of the leading three jets. Again, the quantity considers only the leading few jets to avoid distortions caused by noise.
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calculations; the predictions fail as they approach this limit. The left-hand side of the distributions shows a region where resurnmation might have a large effect in the predictions. Both of these effects are larger than the initial estimate of the uncertainties. 430 < H13 1/2 of their energy due to splitting. Clearly, this means that there is a limit t o the depth of calorimetry which one need not exceed.
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Figure 29. Number of jets with energy greater than the missing energy for a 500 GeV gluon jet for 10,000 generated gluon jets14.
4.3. Signal Speed
The LHC operates with bunch crossings every 25 nsec. At design luminosity there are 20 minimum bias events on the average within each bunch crossing. Therefore, the pulse formation time of LHC calorimetry needs to be < 25 nsec, but no faster. The results of a vigorous R&D program are that LHC calorimetry, both liquid argon and scintillator based, is fast enough to minimize pileup effects at the LHC since all calorimeter signals at the LHC are contained in 1-2 bunching crossings. N
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The pulse shaping for a liquid argon calorimeter is shown in Fig. 30. If the source capacity can be controlled (ATLAS accordi~n’~), then a pulse shape with width less than a single bunch crossing can be obtained. The impulse response16 of a hybrid photodiode (HPD) is shown in Fig. 31. The HPD used in CMS for the hadron calorimeter is sufficiently fast to contain the pulse within 25 nsec. Note that both the accordion electrode structure and the HPD are the fruits of the LHC program of R&D. 4.4. Energg/Mass Error
In searches for new physics, jet measurement and jet-jet invariant mass are crucial elements. For example, the Higgs decay into b quark pairs is the preferred search mode at CDF and DO in Run 11. In order to understand the optimal search strategy at CMS a series of Monte Carlo studies17 were done in order to identify the elements contributing to the mass error. For example, at low 13% , was found in events PT, Z -+ JJ, a fractional mass error of, dM/M without final state radiation (FSR). The contributions to the mass error are shown in Fig. 32. The total mass error is obtained by adding the errors shown in the “pie” chart in quadrature.
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Figure 33. Fractional mass error as a function of jet cone radius for crossings with and without the full LHC pileup of minimum bias events for decays of 2 with high PT into dijets.
Figure 32. Contributions to the fractional mass error for 2 decays into dijets (light quarks only). The contributions should be added in quadrature in order to find the total error.
The FSR is clearly the biggest effect. Ideally a cone could be chosen t o be large enough to contain the jet fragments. However, often the parton itself radiates wide angle and hard gluons prior to hadronization. This process is intrinsic t o the physics and can only be constrained by using very large cone radii. Increasing the cone size would reduce the effects of fragmentation/radiation at wide angles with respect to the jet axis. However, the cone size cannot increase too much or the fluctuations in the underlying event energy found within the cone become large. The plot of Fig. 32 refers to an optimized cone size, one which minimizes the overall mass resolution. At that cone radius the underlying event is the second largest error ( R 0.7) while the competing fragmentation effect is the third largest. Calorimeter resolution is a minor effect. At high luminosity (LHC) there is a minimum dM/M at a reduced cone radius, R 0.618because the pileup due to minimum bias events adds t o the underlying event energy. The optimization balancing jet fragments falling out of cone with inclusion of underlying event and pileup events energy and the accompanying fluctuations shifts to a smaller cone size. Pileup is small for “boosted” Z -+ JJ if a cone radius R 0.6 is used, as seen in Fig. 33. Note that, in this study there was no FSR, so that the mass resolution was only , dM/M 9% for “boosted” Z. Pileup is not the dominant effect. The dominant effect of FSR is illustrated in Fig. 34. Radiation is, indeed, N
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Figure 34. Distribution of the ratio of the reconstructed dijet mass to the generated mass. a) no FSR, b) FSR turned
soft and collinear on average. However, there is multiple gluon emission and there is always a finite probability to emit a hard gluon at a large angle. The ratio of reconstructed to generated mass, MJJ/Mo, for dijets in CMS (Z decays) with and without FSR are shown. The dominant effect of FSR is clear. The d(M/Mo)/(M/Mo) r.m.s. in the fractional mass error rises from 11%to 19%, and the distribution shifts to smaller MJJ/MO due to radiation outside the jet cone. A radiative low mass tail also becomes evident. It is difficult in CMS to reduce the effects due to FSR by increasing the cone to include the radiated energy since that would include too much energy from the underlying event and pileup events.
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5. Future Developments and New Physics
Clearly, future progress in calorimetry for high energy physics will be the result of a comprehensive program of R&D. Higher mass (see Fig. 1)will mean the use of higher luminosity which, in turn, means there is a need to address increased radiation damage and occupation (pileup). The fundamental 2 body production rate goes as square of mass as does the needed luminosity, L , in the best case which occurs when x is 1 TeV and an angular resolution < 1 deg. The ARGO-YBJ detector, with an energy threshold 100 GeV, will employ a single layer of RPC’s covering an area of 6500 m2.
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The ability to measure the flux of extraterrestrial neutrinos offers a unique window to the astrophysical processes of the universe. Neutrinos are unaffected by magnetic fields and propagate virtually unattenuated. Thus, astronomy using neutrinos promises to expand the study of astrophysical phenomena, particularly in energy ranges where photon astronomy is limited due to absorptive effects, e.g. at energies 2 1 TeV. Neutrinos are difficult to measure because
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of their small interaction cross sections and the existence of large backgrounds due to sources such as the much more numerous products of cosmic ray interactions. These lead to the need for large detector volumes to obtain an appreciable event rate and requirements to reduce the backgrounds such as locating the neutrino detector deep underground. eV (1.95K relic The energies of astrophysical neutrinos range from neutrinos) to > 1020 eV for neutrinos from the interaction of UHECR with the cosmic microwave background. Between these energy extremes are neutrinos from the Sun ( E , 5 15 MeV), neutrinos from supernovae (< E, >% 10’s of MeV), atmospheric neutrinos which follow the spectrum of the inducing cosmic rays, and high energy neutrinos with ( E , 2 100 GeV). In the arena of Solar neutrino measurements, the Super-Kamiokande experiment37 (water Cherenkov detector) is to be rebuilt, the Sudbury Neutrino O b ~ e r v a t o r y(heavy ~~ water Cherenkov detector) will continue to take data, and the ICARUS experiment39 (liquid argon TPC) is to be constructed. The next generation of solar neutrino experiments have a focus of reducing the neutrino energy threshold to well below 1 MeV in order to measure the monoenergetic neutrinos from the Be solar process and obtain better determination of the neutrino oscillation parameters40. The reduced energy threshold also allows for measurement of neutrinos from the p p process which is more insensitive to solar modeling. The BOREXINO experiment41 will use 300 tons of liquid scintillator as the neutrino target and detector to achieve an energy threshold of 250 keV and an energy resolution of 5% at 1 MeV. KAMLAND42 employs 1000 tons of liquid scintillator and plans to extend its primary science of a reactor neutrino oscillation search to solar neutrinos. Other experiments include the LENS experiment43 which will use Yb loaded liquid scintillator, HERON44using superfluid helium, and HELLAZ45which will employ a helium gas TPC. Galactic supernovae occur with a frequency of one every 10-30 years. Thus, experiments sensitive to the observation of neutrinos from supernovae need to be designed for long, many-year operation in order to guarantee an observation. Currently operating experiments such as Super-Kamiokande and SNO are sensitive to neutrinos from supernovae. In addition to the future Solar neutrino experiments that will have supernovae-neutrino sensitivity, multi-ton experiments have been proposed to use high-Z neutrino targets and detect the products, particularly neutrons, from the neutrino-nucleus interactions. The OMNIS experiment46 will use iron and lead as the target materials. The different energy thresholds for the various interaction channels leads to a methodology to distinguish between v, charged-current and neutral current interactions as well as ux neutral current interaction^^^. The event rate dependence of
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the different interaction channels leads to a sensitivity to neutrino oscillations. OMNIS and another experiment of this type known as LAND could be located at a dedicated, underground neutrino laboratory. At energies 2 1 TeV, astrophysical objects such as Active Galactic Nuclei (AGNs)~*and Gamma Ray Bursts4’ could be a source of neutrinos via the decay of mesons produced from an accelerated hadronic component. However, detectors with 1 km3 of water-equivalent volume are required in order t o obtain an appreciable event rate50. At these energies, the neutrinos can be detected by measuring the Cherenkov radiation of the interaction products using the technique pioneered by the DUMAND51 and BAIKAL52 experiments. The ICECUBE experiment53 will expand upon the successful AMANDA array54 by deploying 80 strings totalling 4800 PMTs to instrument 1 km3 of Antarctic ice. The energy resolution from measurements of the muon from vcl interactions is expected t o be O.SIog(E,) with an angular resolution of 1 deg. For shower-type events, e.g. v, interactions, the energy resolution is expected to improve while the angular resolution will be degraded. Several experiments are planned to construct large, underwater neutrino telescopes with an eventual volume 1 km3. These include ANTARES55, NESTER56,and NEM057. These experiments have a nominal energy threshold of 1 TeV and a planned upgrade to the BAIKAL experiment would provide neutrino measurements at lower energies. As the Cherenkov light-scattering length is much longer in water than ice, the underwater experiments expect an angular resolution 0.5 deg for muons from vcl interactions. These experiments will also have a sensitivity to bursts of lower energy neutrinos such as ve from supernovae. At energies 2 1 PeV, the neutrino and antineutrino cross sections become virtually equivalent5*. Furthermore, the average energy of the lepton in a neutrino interaction is more than 70% of the initial neutrino energy, increasing to 80% at E, = lo2’ eV with the remaining energy given to a hadronic shower at the neutrino interaction point. These kinematics lead to an unique, “double-bang” signature for high energy, charged-current v, interactions where the produced r-lepton has a sufficient Lorentz boost to lead t o a separated shower induced by the r decay5’. Thus experiments, such as ICECUBE, have a methodology to detect v, events that could arise from the oscillations of astrophysical v p neutrinos. The importance of v, sensitivity is enhanced when considering the fact that the Earth attenuates neutrinos with energies 2 40 TeV, but v, can effectively propagate through the Earth, albeit with degraded energy, due to regeneration60. Neutrinos a t ultra-high energies, 10” eV, are expected from the decay of pions produced from the interaction of UHECR with the microwave background61, i.e the GZK effect. Furthermore, the speculative, “top-down”
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processes, such as topological defects62 or Z - b u r ~ t sthat ~ ~ , are proposed t o be the source of the trans-GZK cosmic rays also predict hard neutrino spectra at ultra-high energies. The next generation UHECR experiments, Auger, Telescope Array, EUSO, and OWL, monitor a large atmospheric volume and thus have a sensitivity to ultra-high energy, neutrino induced airshowers. These events can be separated from the more numerous UHECR events by using the fact that neutrino-event interactions can occur much deeper in the atmosphere. Thus deep, horizontal airshowers offer a signature for ultra-high energy neutrino interactions. An ingenious method for detecting high energy u, interactions in the Earth (or moon) uses the radio Cherenkov signal generated by the subsequent electromagnetic shower64. Proposed by Askaryan, the intense coherent, Cherenkov radio pulse is caused by a 20% charge asymmetry in developing electromagnetic showers and the coherence leads to an energy dependent power enhancement. The Askaryan effect has been verified in a SLAC test beam65 and has been employed by the RICE array66 in Antarctica to search for high energy u, interactions in the ice and the GLUE experiment? which uses radio telescopes to search for ultra-high energy neutrino interactions in the moon. The strength of the radio Cherenkov technique is that for materials with good radio transmission properties, extremely large neutrino detectors can be instrumented. The use of 25 km3 salt domes is being investigated as well as flying a radio Cherenkov experiment on a long duration balloon over Antarctica. The latter experiment, ANITA64, would have lo6 km3 of ice as the neutrino fiducial volume and be sensitive to neutrinos above 1017 eV. The experiment is expected t o have an energy resolution of 1 at lo1* eV and an angular resolution of 10 deg. The potential performance combination of the relatively low energy threshold and large neutrino-detection aperture of these experiments surpasses the neutrino detection capabilities of other techniques for ultra-high energy neutrinos.
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5 . Summary
Future experiments in the area of cosmic rays will extend charged-particle spectroscopy measurements and provide a sensitive search for antimatter in the cosmic radiation (PAMELA, AMS) , provide elemental composition measurements t o 1015 eV (ATIC, CREAM, and possibly ACCESS), and try to unravel the mystery of the source of ultra-high cosmic rays (AUGER, Telescope Array, EUSO, OWL). Future gamma ray missions promise to study the phenomena of gamma ray bursts with superb angular resolution and sensitivity (SWIFT) and close the energy window that exists between 20 GeV and 1
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TeV (GLAST, Air Cherenkov Telescopes, MILAGRO) while making dramatic improvements in angular resolution and sensitivity. The potential to perform high energy neutrino astronomy will be realized with the construction of km3 neutrino detectors (ANTARES, NESTER, ICECUBE). These combined with the neutrino measurement potentials of the UHECR experiments and experiments that employ the radio Cherenkov technique (ANITA) promise to open a new window to the astrophysical processes of the universe. References 1. http://www.roma2.infn.it/research/comm2/caprice/ 2. http: / /WiZard.roma2.infn.it/pamela/ 3. V. Bonvicini, these proceedings 4. R. Kossakowski and P. Maestro, these proceedings 5. J. Isbert and T.L. Wilson, these proceedings 6. 0. Ganel, these proceedings 7. http://lheawww.gsfc.nasa.gov/ACCESS/ 8. for an overview see http://hires.physics.utah.edu/background.html 9. http://hires.physics.utah.edu/flyseye.html 10. http://iklaul.fzk.de/KASCADEhome.html 11. http://hires.physics.utah.edu/ 12. http://www-aken0.icrr.u-tokyo.ac.jp/AGASA/ 13. A.K. Tripathi, these proceedings 14. http://www-ta.icrr.u-tokyo.ac.jp/ 15. J. Linsley, Proc. 19th ICRC (La Jolla), 3, 438 1985) 16. K. Arisaka, these proceedings 17. http://owl.gsfc.nasa.gov/ 18. F.W. Stecker, astro-ph/0010015 19. http://swift.gsfc.nasa.gov/ 20. http://lheawww.gsfc.nasa.gov/docs/gamcosray/EGRET/egret.html 21. http://agile.mi.iasf.cnr.it/Homepage/ 22. http://www-glast.stanford.edu/ 23. A. Chekhtman and R. Terrier, these proceedings 24. G.K. Skinner, Astronomy and Astrophysics, 375, 691 (2001) 25. http://maxim.gsfc.nasa.gov/ 26. http://egret.sao.arizona.edu/index.html 27. http://hegral.mppmu.mpg.de/MAGICWeb/ 28. http://www.mpi-hd.mpg.de/hfm/HESS/HESS.html 29. http://icrhpS.krr.u-tokyo.ac.jp/ 30. F. Krennrich, these proceedings 31. http://hep.uchicago.edu/-staceel 32. http://wwwcenbg.in2p3.fr/extra/Astroparticule/celeste/e-index.html 33. http: / /hegral .mppmu.mpg.de/GRAAL/ 34. http://solartwo.ucr.edu/solar2.html 35. http://www.lanl.gov/milagro/ 36. http://wwwl.na.infn.it/wsubnucl/cosm/argo/argo.html
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http://www.phys.washington.edu/-superk/ http://www.sno.phy.queensu.ca/ http://www.aquila.infn.it/icarus/ http://www.sns.ias.edu/Nj.b/ http://almime.mi.infn.it/ http://www.awa.tohoku.ac.jp/html/KamLAND/index.html http :/ flens.in2p3.fr/ http://www.physics.brown.edu/research/cme/heron/index.html http://sgl.hep.fsu.edu/hellaz/ http://www.physics.ohio-state.edu/OMNIS/ J.J. Zach et al., NIM A484, 194 (2002) F. Stecker and M. Salamon, Space Sci. Rev. 75, 341 (1996) E. Waxman and J. Bahcall, Phys.Rev.Let. 78, 2292 (1997) F. Halzen, astro-ph/9605014 A. Roberts, Rev.Mod.Phys. 64, 259 (1992) http://www.ifh.de/baikal/baikalhome.html J. Lamoureux, these proceedings http://amanda.berkeley.edu/amanda/amanda.html http://antares.in2p3.fr/ http://www.uoa.gr/Nnestor/ http://nemoweb.lns.infn.it/ R. Gandhi et al., Phys.Rev. D58, 093009 (1998) J.G. Learned and S. Pakvasa, hep-phf9408296 F. Halzen and D. Saltzberg, Phys.Rev.Lett. 81, 4305 (1998) R. Engel et al., Phys.Rev. D64 093010 (2001) G. Sigl et al., Phys.Rev. D59, 043504 (1999) T.J. Weiler, Astropart.Phys. 11, 303 (1999) D. Saltzberg, these proceedings D. Saltzberg et al., Phys.Rev.Lett. 86, 2802 (2001) S. Razzaque, these proceedings http://www.physics.ucla.edu/Nmoonemp/public/index.html D. Saltzberg, these proceedings
Conference Pictures
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AUTHOR INDEX
Abbiendi, G., 287 Adams, J. H., 89 Adamson, P., 428, 436 Ahn, H. S., 89, 133 Akchurin, N., 521 Akgun, U., 521 Alford, R., 133 Alner, J., 428, 436 Aloisio, A., 388 Ambrosino, F., 388 Anderson, B., 428, 436 Andersen, V., 95 Antonelli, A., 388 Antonelli, M., 388 Aspell, P., 621 Atramentov, O., 497 Attal, A., 557 Attree, D., 428, 436 Auffray, E., 240 Ayan, S., 521
Bencivenni, G., 388 Benen, A., 549 Bertolucci, S., 388 Besson, A., 679 Bini, C., 388 Bloch, P., 621 Bloise, C., 388 Bocci, V., 388 Boezio, M., 101 Bonvicini, V., 101 Borkar, S., 621 Bossi, F., 388 Boudry, V., 652 Branchini, P., 388 Breidenbach, M., 304 Breton, D., 627 Brient, J.-C., 309, 747 Bruecken, P., 521 Bulychjov, S. A,, 388 Cadoux, F., 108 Caloi, R., 388 Campana, P., 388 Capon, G., 388 Carboni, G., 388 Carminati, F., 95 Casarsa, M., 388 Casavola, V., 388 Case, G., 89 Cataldi, G., 388 Cavallari, F., 223 Cavalli-Sforza, M., 531 Ceradini, F., 388 Cervelli, F., 108, 114, 388 Cevenini, F., 388
Biischer, M., 215 Bacci, C., 388 Bacelar, J., 215 Bailly, Ph., 652 Bamberger, A., 806 Barbi, M., 401 Barker, M., 428, 436 Barney, D., 621 Barrelet, E., 652 Bashindzhagyan, G., 89 Bassler, U., 413 Beatty, J. J., 133 Belias, A., 428, 436 Benchekroun, D., 331
889
890
Chambert-Hermel, V., 108 Chang, J., 89 Chekanov, S., 806 Chekhtman, A., 121, 127 Chen, G., 108, 114 Chen, H., 108, 114 Chiche, R., 652 Chiefari, G., 388 Choi, M. J., 133 Christl, M., 89 Ciambrone, P., 388 Coignet, G., 108, 114 Collot, J., 274 Conetti, S., 388 Coutu, S., 133 Crone, G., 428, 436 Currrat, C. A., 345 Danagoulian, S., 479 De La Taille, Ch., 652 De Lucia, E., 388 De Robertis, G., 388 De Simone, P., 388 De Zorzi, G., 388 Deiters, K., 231 Dell’Agnello, S., 388, 563 Deng, Q., 190,491 Denig, A., 388 Di Domenico, A., 388 Di Donato, C., 388 Di Falco, S., 108, 114, 388 Djannati-Atai, A., 127 Doria, A., 388 Doring, W., 215 Drake, G., 806 Dreucci, M., 388 Dubois, J. M., 108 Dumanoglu, I., 521 Durkin, T., 428, 436 Duval, P.-Y., 665 Duvernois, M. A., 133
Elias, J., 605 Empl, A., 95 Erriquez, O., 388 Eschrich, I. G., 658 Eskut, E., 521 Falchini, E., 108, 114 Falk, E., 428, 436 Farilla, A., 388 Fasso, A., 95 Fazely, A. R., 89 Felici, G., 388 Felt, N., 428, 436 Fenyvesi, A., 521 Ferrari, A., 95, 388 Ferrer Ribas, E., 613 Ferrer, M. L., 388 Fincke-Keeler, M., 712 Finocchiaro, G., 388 Forti, C., 388 Fougeron, D., 108 Fouque, N., 108 Fournier, D., 17 Franceschi, A., 388 Franzini, P., 388 Frey, R. E., 54, 304 Freytag, D., 304 Futo, E., 95 Gottlicher, P., 296 Gallin-Martel, M. L., 274 Ganel, O., 89, 133 Gasparian, A., 208 Gataullin, M., 385 Gatti, C., 388 Gauzzi, P., 388 Giovannella, S., 388 Girard, L., 108, 114 Go, A., 621 Gorini, E., 388 Goy, C., 108, 114
891
Grahl, J., 231 Grancagnolo, F., 388 Granger, D., 89 Graziani, E., 388 Green, D., 837 Grove, J. E., 127 Gunasingha, R., 89 Guzik, T. G., 89 Haller, G., 304 Hamer, A., 442 Han, S. W., 388 Han, Y. J., 89 Hanson, K. D., 452 Harris, P., 428, 436 Hejny, V., 215 Henriques, A., 532 Hermel, R., 108 Hoek, M., 215 HofEmann, D., 665 Hryn'ova, T., 175 Hu, T., 459 Huang, H.-C., 161 Huffer, M., 304 Incagli, M., 388 Ingram, Q., 231 Ingrosso, L., 388 Isbert, J., 89, 95 Jan, S., 274 Jenner, L., 428, 436 John, M., 127 Johnson, W. N., 127 Jones, G . M., 728 Karpetian, G., 331 Katta, S., 544 Kayis-Topaksu, A., 521 Kellogg, R. G., 287 Kiiskinen, A., 798 Kim, H. J., 89, 133
Kim, K. C., 89, 133 Kim, S. K., 89, 133 Kiryunin, A. E., 331, 354, 720 Kish, J., 331, 354 Kistenev, E., 584 Kluge, W., 388 Koca, N., 521 Koch, H. R., 215 Kochetkov, V., 584 Kocian, M., 167 Korbel, V., 591 Kordas, K., 331 Kordosky, M., 428, 436 Korolko, I., 584 Korolkov, I., 538 Kossakowski, R., 108, 114 Kouznetsov, E., 89 Krane, J., 786 Krennrich, F., 139 Krizmanic, J . F., 867 Kronqvist, I., 231 Kuhlmann, S., 806 Kulikov, V., 388 Kunori, S., 375 Kuo, C., 388 Kuznetsov, A., 231 Lohner, H., 215 Lacava, F., 388 Lalwani, S., 621 Lanfranchi, G., 388 Lang, K., 428,436 Lebbolo, H., 652 Lebedev, A., 428, 436 Lecoq, P., 262 Lee, K., 95 Lee, M. H., 133 Lee, R., 428, 436 Lee-F'ranzini, J., 388 Leltchouk, M., 331 Leone, D., 388
892
Li, Z. K., 491 Liao, J. Y., 190 Lieunard, B., 108 Litvin, V., 325 Liu, D. T., 469 Liu, L., 133 Liu, Z., 108, 114 Lobban, O., 421, 814 Loch, P., 331, 354 Lofstedt, B., 621 Lomtadze, T., 108, 114 Longley, N., 428, 436 Lu, F., 388 Lu, Y., 108, 114 Lutz, L., 133 Miiller, S., 388 Machner, H., 215 Maestro, P., 108, 114 Magill, S., 806 Majatsky, I., 584 Makonyi, K., 521 Malinine, A., 133 Mao, R. H., 190 Marrocchesi, P. S., 108, 114 Marshak, M., 428, 436 Martemianov, M., 388 Martin, F., 607 Martin, P., 274 Matsyuk, M., 388 Mazini, R., 331, 354 Mei, W., 388 Melnikov, E., 584 Merlo, J. P., 521 Merola, L., 388 Messi, R., 388 Michael, D., 428, 436 Minard, M. N., 739 Minnick, S. A., 133 Miramonti, L., 570 Miscetti, S., 388
Miyabayashi, K., 394 Miyagawa, P., 428, 436 Mocchiutti, E., 101 Moreau, F., 652 Morgunov, V. L., 70 Morse, R., 428, 436 Moses, W. W., 251 Moulson, M., 388 Mualem, L., 578 Murtas, F., 388 Musgrave, B., 806 Musienko, Y., 231 Musser, J., 428, 436 NgmeEek, S., 538 Nakamura, I., 793 Napolitano, M., 388 Naqvi, S. A., 89 Nedosekin, A., 388 Negroni, S., 331 Nelson, C. A., 644 Nevski, P., 584 Newman, H., 325 Nguyen, F., 388 Nichol, R., 428, 436 Nicholls, T., 428, 436 Novotny, R., 215 Noyak, D., 521 Nutter, S., 133 Oliver, J., 428, 436 Onel, Y., 504, 521 Onengut, G., 521 Paganini, P., 339 Palutan, M., 388 Panasyuk, M., 89 Panov, A., 89 Paoletti, R., 108, 114 Paoluzi, L., 388 Park, I. H., 133 Parnell, T., 87
893
Parrour, G., 331 Parua, N., 687 Pasqualucci, E., 388 Passalacqua, L., 388 Passeri, A., 388 Patera, V., 388 Pearce, G., 428, 436 Peisert, A., 621 Petrolo, E., 388 Petyt, D., 428, 436 Pilo, F., 108, 114 Pinsky, L., 95 Polatoz, A., 521 Pontecorvo, L., 388 Pretzl, K., 3 Price, B., 89 Primavera, M., 388 Proga, M., 428, 436 Proudfoot, J., 806
Qu, X. D., 190 Ranft, J., 95 Razzaque, S., 515 Rebel, B., 428, 436 Ren, G. H., 491 Renard, Ch., 652 Renker, D., 231 Repond, J., 806 Reucroft, S., 231 Reynaud, S., 621 Rodier, S., 695 Rosier-Lees, S., 108, 114 Ruggieri, F., 388 Rusack, R., 231 Russell, J. J., 304 Saakyan, R., 428, 436 Sajot, G., 679 Sakhelashvili, T., 231 Sala, P., 95
Salihagic, D., 331, 354 Samsonov, G., 89 Santangelo, P., 388 Santovetti, E., 388 Saracino, G., 388 Savine, A., 781 Schacht, P., 677 Schamberger, R. D., 388 Schiavon, P., 101 Schindhelm, E., 133 Schmidt, I., 521 Schmidt, W. K. H., 89 Schwanenberger, C., 761 Scian, G., 101 Sciascia, B., 388 Sciubba, A,, 388 Scuri, F., 388 Seez, C., 323 Seligman, W., 331 Seo, E. S., 89, 133 Serin, M., 521 Seyfarth, H., 215 Sfiligoi, I., 388 Shaw, T. M., 644 Shen, D. Z., 190, 491 Shevchenko, S., 325 Shwartz, B. A,, 182 Sina, R., 89 Singovski, A., 231 Smith, C., 428, 436 Sokolskaya, N., 89 Soukharev, A., 331 Spadaro, T., 388 Specka, A. E., 652 Spiriti, E., 388 Sriharan, A., 814 Stanek, R.,806 Stewart, M., 89 Stroher, H., 215 Striienec, P., 331, 354
894
Strom, D., 285, 287 Sullivan, P., 428, 436 Swain, J., 231 Swordy, S. P., 43, 133 Tonnesmann, M., 773 Terrier, R., 127 Thomas, J., 428, 436 Tong, G. L., 388 Torii, H., 409 Tortora, L., 388 Tournefier, E., 274 Tripathi, A. K., 151 Turini, N., 108, 114 Vacchi, A., 101 Vahle, P., 428, 436 Valente, E., 388 Valente, P., 388 Valeriani, B., 388 Valle, G., 108, 114 Vallee, C . , 665 Vallereau, A., 652 Varanda, M. J., 361 Venanzoni, G., 108, 114, 388 Veneziano, S., 388 Ventura, A., 388 Vialle, J. P., 108, 114 Videau, H., 309, 747 Voronin, A., 89 Wang, J. Z., 89, 133 Weber, A., 428, 436
Wefel, J. P., 89, 95 Wei, Q., 469 White, S., 489 Wielers, M., 367 Wigmans, R., 814 Wilson, T., 95 Wing, M., 767 Wisniewski, N., 325 Wojcicki, S., 428, 436 Woody, C . , 249, 584 Wronska, A., 215 Wu, J., 89, 133 Xia, L., 459 Xu, G., 388 Yan, D. S., 190 Yin, Z. W., 190 Yoshida, R., 806 Yu, G. W., 388 Yu, Z., 108, 114 Zampa, G., 101 Zampa, N., 101 Zatsepin, V., 89 Zerwas, D., 703 Zeyrek, M., 521 Zhang, L., 190, 469 Zhu, K., 469 Zhu, R. Y., 190, 459, 469 Zhuang, H., 108, 114
LIST OF PARTICIPANTS ABBIENDI
Giovanni
INFN
Bologna
Italy
ARISAKA
Katsushi
UCLA
USA
ATRAMENTOV
Oleksiy
Iowa State Univ.
USA
ATTAL
Alon
UCLA
USA
AUFFRAY
Etiennette
CERN
Switzerland
BAMBERGER
Andreas
ANL/Freiburg Univ.
USA
BARB1
Mauricio
McGill Univ.
Germany
BASHMAKOV
Yuriy
P.N. Lebedev Physical Inst.
Russia
BASSLER
Ursula
LPNHE
France
BENEN
Arno
Univ. of Freiburg
Germany
BESSON
Auguste
I.S.N.
France
BLANCHARD
Rick
Hamamatsu
USA
BOEZIO
Mirko
INFN - Trieste section
Italy
BONVICINI
Valter
INFN
Italy
-
-
Sezione di Trieste
BOUDRY
Vincent
CNRS/INSP3
France
BRETON
Dominique
LAL Orsay
France
CAVALLARI
Francesca
INFN
Switzerland
C AVALLI-SFORZA
Matteo
IFAE - Barcelona
Spain
CHEKHTMAN
Alexandre
NRL/GMU
USA
CHOUDHARY
Brajesh
Caltech
USA
COLAS
Jacques
LAPP
France
CURRAT
Charles
LBNL
USA
DANAGOULIAN
Samuel
NC A&T State Univ.
USA
DELL’AGNELLO
Simone
INFN
Italy
DENG
Shanghai Inst. of Ceramics
P.R. China
DI CREDICO
Qun Alessandra
LNGS/INFN
Italy
DYCHKANT
Alexandree
Northern Illinois Univ.
USA
EIGEN
Gerald
U. Bergen
Norway
ELIAS
John
Fermilab
USA
ELLIOT
Lipeles
Caltech
USA
EREDITATO
Antonio
INFN Napoli
Italy
FABBRI
Franco
Frascati - INFN
Italy
895
896 F E R R E R RIBAS
Esther
SPP-CEA-Saclay
France
FINCKE-KEELER
Margret
Univ. of Victoria
Canada
FLYCKT
Esso
Photonis
France France
FOURNIER
Daniel
LAL-Orsay
FREY
Raymond
Univ of Oregon
USA
GANEL
Opher
Univ. of Maryland
USA
G ASPARIAN
Ashot
NC A&T State Univ.
USA
GATAULLIN
Marat
Caltech
USA
GATTI
Claudio
Universita’ Pisa and INFN
Italy
GO
Apollo
CERN
Switzerland
GOETTLICHER
Peter
DESY
Germany
GOUGH ESCHRICH
Ivo
Imperial College
USA
GREEN
Daniel
Fermilab
USA
HAMER
Andre
Los Alamos National Lab.
USA
HANSON
Kael
Univ. of Pennsylvania
USA
HENRIQUES
Ana
CERN
Switzerland
HITLIN
David
Caltech
USA
HOFFMANN
Dirk
DESY
Germany
HRYN’OVA
TETIANA
SLAC
USA
HUANG
Hsuan-Cheng
National Taiwan Univ.
Rep. of China Italy
INTROZZI
Gianluca
Univ. of Pavia - Italy
ISBERT
Joachim
Louisiana State Univ.
USA
JOHANN
Collot
ISN
France
JONES
Gary
Caltech
USA
JOO
Kyung Kwang
U of Toronto
Canada
KATSAVOUNIDIS
Erik
MIT
USA
KATTA
SUDHAKAR
TATA INSTITUTE
India
KIISKINEN
Ari
Helsinki Inst. of Physics
Switzerland
KIRY UNIN
Andrei
Max-Planck-Inst. for Physics
Germany
KOCIAN
Martin
SLAC
USA
KORBEL
Volker
DESY
Germany
KOSSAKOWSKI
Roman
L A P P - IN2P3
France
KRANE
John
Iowa State Univ.
USA
KRENNRICH
Frank
Iowa State Univ.
USA
KRIZMANIC
John
USRA/NASA/GSFC
USA
a97 KUNORI
Shuichi
U. of Maryland
USA
LAMOUREUX
Jodi
LBNL
USA
LECOMTE
Pierre
ETHZ
Switzerland
LECOQ
Paul
CERN
Switzerland
LIAO
Jingying
Shanghai Inst. of Ceramics
P.R.China
LOBBAN
Olga
Texas Tech Univ.
USA
LOCH
Peter
Univ. of Arizona
USA
LOKAJICEK
Milos
Acad. of Sci. Prague
Czech Republic
LOS
Sergey
Fermilab
USA
LUDWIG
Jens
Univ. Freiburg
Germany
MAGILL
Stephen
Argonne National Lab.
USA
MA10
Amelia
FCUL and LIP/Lisbon
Portugal
MANSOULIE
Bruno
DAPNIA-SACLAY
France
MA0
Rihua
Caltech
USA
MARTIN
Franck
L P C Clermont Ferrand
France
MELCHER
Charles
CTI, Inc.
USA
MICHAEL
Douglas
C alt ech
USA
MINARD
Marie-Noelle
LAPP
France
MIRAMONTI
Lino
Milano Univ.
Italy
MIYABAYASHI
Kenkichi
Nara Women’s Univ.
Japan
M 0RG U N OV
Vasily
DESY-ITEP
Germany
MOSES
William
LBL
USA
MUALEM
Leon
Univ. of Minnesota
USA
NAKAMURA
Isamu
Univ. of Pennsylvania
USA
NELSON
Charles
Fermilab
USA
NEMECEK
Stanislav
Acad. Sci. Prague
Czech Republic
NICHOL
Ryan
Univ. College London
UK
NOVOTNY
Rainer
Univ. Giessen
Germany
OBERLACK
Horst
MPI fuer Physik
Germany
ONEL
Yasar
Univ. of Iowa
USA
PAGANINI
Pascal
LLR Ecole Polytechnique
France
PAOLO
Maestro
INFN-Pisa & Univ. of Siena
Italy
PAPPAS
Stephen
C a1t ech
USA
PARNELL
Thomas
Univ. of AL in Huntsville
USA
PARUA
Nirmalya
SUNYQ Stony Brook
USA
898 PORTER
Frank
Caltech
USA Switzerland
PRETZL
Klaus
Univ. Bern
RAVEL
Akhmetshin
Novosibirsk INP
Russia
RAZZAQUE
Soebur
Univ. of Kansas
USA
RODIER
Stephane
UAM
Spain
RUSACK
Roger
The Univ. of Minnesota
USA
SALTZBERG
David
UCLA
USA
SAVINE
Alexandre
Univ. of Arizona
USA
SCHACHT
Peter
Max-Planck-Inst. fur Physik
Germany
SCHWANENBERGER
Christian
DESY
Germany
SEEZ
Chris
Imperial, London
UK
SHEN
Dingzhong
Shanghai Inst. of Ceramic
P.R. China
SHEVCHENKO
Sergey
Caltech
USA
SHWARTZ
Boris
Budker INP
Russia
SIMON
Swordy
Univ. of Chicago
USA USA
SKUJA
Andris
Univ. of Maryland
STROM
David
Univ. of Oregon
USA
TERRIER
Regis
P C C Collbge de France
France
TERRON
Juan
Universidad Autonoma Madrid
Spain
TOENNESMANN
Matthias
MPI Munich
Germany
TORI1
Hisayuki
Kyoto Univ./RIKEN
USA
TRIPATHI
Arun
UCLA
USA
TU
Qinwei
Shanghai Inst. of Ceramics
P.R. China
VAHLE
Patricia
Univ. of Texas a t Austin
USA
VARANDA
Maria
LIP
Portugal
VIDEAU
Henri
LLR Ecole polytechnique/IN2PB
France
WE1
Qing Sebastian
Caltech
USA
WHITE
BNL
USA
WIELERS
Monika
TRIUMF
Canada
WIGMANS
Richard
Texas Tech Univ.
USA
WILKINSON
Richard
Caltech
USA
WILSON
Thomas
NASA, Johnson Space Center
USA
WING
Matthew
Bristol Univ., UK
Germany
WISNIEWSKI
William
SLAC
USA
WOODY
Craig
BNL
USA
899
wu
Weimin
XIA
Lei
Caltech
USA
YOSHIDA
Rik
Argonne National Lab.
USA
YOSHIMURA
Sam
Kuraray America, Inc.
USA
ZERWAS
Dirk
LAL-Orsay
fiance
ZHANG
Liyuan
Caltech
USA
ZHOU
Li
IHEP Beijing
P.R. China
ZHU
Ren-yuan
Caltech
USA
ZUTSHI
Vishnu
Northern Illinois Univ.
USA
Fermilab
USA