Published January 1, 2021
| Version v1
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The DAQ system of the 12,000 channel CMS high granularity calorimeter prototype
Creators
- 1. Bogazici Univ, TR-34342 Istanbul, Turkey
- 2. Georgian Tech Univ, 77 Kostava Str, GE-0175 Tbilisi, Georgia
- 3. Natl Cent Univ Taipei NCU, 300 Jhongda Rd, Jhongli 32001, Taiwan
- 4. Int Intergovt Org, Joint Inst Nucl Res JINR, 6 Joliot Curie St, Moscow 141980, Russia
- 5. Texas Tech Univ, Lubbock, TX 79409 USA
- 6. Univ Iowa, 203 Van Allen Hall, Iowa City, IA 52242 USA
- 7. Carnegie Mellon Univ, 5000 Forbes Ave, Pittsburgh, PA 15213 USA
- 8. Brown Univ, 182 Hope St, Providence, RI 02912 USA
- 9. Fermilab Natl Accelerator Lab, POB 500, Batavia, IL 60510 USA
- 10. Cukurova Univ, TR-01330 Adana, Turkey
- 11. Russian Acad Sci, Inst Nucl Res, 60th Oct Anniversary Prospekt 7A, Moscow 117312, Russia
- 12. CERN, Esplanade Particules 1, CH-1211 Geneva 23, Switzerland
- 13. Deutsch Elektronen Synchrotron DESY, Notkestr 85, D-22607 Hamburg, Germany
- 14. Univ Maryland, College Pk, MD 20742 USA
- 15. Natl Tech Univ Athens, Heroon Polytechneiou St, Athens 15780, Greece
Description
The CMS experiment at the CERN LHC will be upgraded to accommodate the 5-fold increase in the instantaneous luminosity expected at the High-Luminosity LHC (HL-LHC) [1]. Concomitant with this increase will be an increase in the number of interactions in each bunch crossing and a significant increase in the total ionising dose and fluence. One part of this upgrade is the replacement of the current endcap calorimeters with a high granularity sampling calorimeter equipped with silicon sensors, designed to manage the high collision rates [2]. As part of the development of this calorimeter, a series of beam tests have been conducted with different sampling configurations using prototype segmented silicon detectors. In the most recent of these tests, conducted in late 2018 at the CERN SPS, the performance of a prototype calorimeter equipped with approximate to 12, 000 channels of silicon sensors was studied with beams of high-energy electrons, pions and muons. This paper describes the custom-built scalable data acquisition system that was built with readily available FPGA mezzanines and low-cost Raspberry Pi computers.
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