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Title: Machine learning for imaging Cherenkov detectors

Journal Article · · Journal of Instrumentation
 [1]
  1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)

Imaging Cherenkov detectors are largely used in modern nuclear and particle physics experiments where cutting-edge solutions are needed to face always more growing computing demands. This is a fertile ground for AI-based approaches and at present we are witnessing the onset of new highly efficient and fast applications. This paper presents novel directions with applications to Cherenkov detectors. In particular, recent advances on detector design and calibration, as well as particle identification are presented.

Research Organization:
Thomas Jefferson National Accelerator Facility, Newport News, VA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Nuclear Physics (NP)
Grant/Contract Number:
FG02-94ER40818
OSTI ID:
1671317
Alternate ID(s):
OSTI ID: 23038358
Report Number(s):
JLAB-PHY--20-3159; DOE/OR/23177-5054; arXiv:2006.05543
Journal Information:
Journal of Instrumentation, Journal Name: Journal of Instrumentation Journal Issue: 02 Vol. 15; ISSN 1748-0221
Publisher:
Institute of Physics (IOP)Copyright Statement
Country of Publication:
United States
Language:
English

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