Simulation and performance of an artificial retina for 40 MHz track reconstruction

Journal Article · Thu Mar 05 00:00:00 EST 2015 · Journal of Instrumentation

DOI:https://doi.org/10.1088/1748-0221/10/03/C03008· OSTI ID:1395479

Abba, A. ^[1]; Bedeschi, F. ^[2]; Citterio, M. ^[1]; Caponio, F. ^[1]; Cusimano, A. ^[1]; Geraci, A. ^[1]; Marino, P. ^[3]; Morello, M. J. ^[3]; Neri, N. ^[1]; Punzi, G. ^[2]; Piucci, A. ^[2]; Ristori, L. ^[4]; Spinella, F. ^[2]; Stracka, S. ^[3]; Tonelli, D. ^[5]

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1. Politecnico and INFN-Milano (Italy)
2. University and INFN-Pisa (Italy)
3. Scuola Normale Superiore and INFN-Pisa (Italy)
4. University and INFN-Pisa (Italy); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
5. European Organization for Nuclear Research (CERN), Geneva (Switzerland)

We present the results of a detailed simulation of the artificial retina pattern-recognition algorithm, designed to reconstruct events with hundreds of charged-particle tracks in pixel and silicon detectors at LHCb with LHC crossing frequency of 40 MHz. Performances of the artificial retina algorithm are assessed using the official Monte Carlo samples of the LHCb experiment. We found performances for the retina pattern-recognition algorithm comparable with the full LHCb reconstruction algorithm.

• Research Organization: Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
• Sponsoring Organization: USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
• Grant/Contract Number: AC02-07CH11359
• OSTI ID: 1395479
• Alternate ID(s): OSTI ID: 22497268
• Report Number(s): FERMILAB-CONF--14-611-CMS; arXiv:1409.0898; 1314984
• Journal Information: Journal of Instrumentation, Journal Name: Journal of Instrumentation Journal Issue: 03 Vol. 10; ISSN 1748-0221
• Publisher: Institute of Physics (IOP)
• Country of Publication: United States
• Language: English

Related Subjects

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
97 MATHEMATICS AND COMPUTING
Pattern recognition
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calibration and fitting methods
cluster finding