Artificial Intelligence for imaging Cherenkov detectors at the EIC

Fanelli, C.; Mahmood, A.

doi:10.1088/1748-0221/17/07/c07011

Artificial Intelligence for imaging Cherenkov detectors at the EIC

Journal Article · Fri Jul 01 04:00:00 EDT 2022 · Journal of Instrumentation

DOI:https://doi.org/10.1088/1748-0221/17/07/c07011· OSTI ID:1979438

Fanelli, C. ^[1]; Mahmood, A.

OSTI

Abstract

Imaging Cherenkov detectors form the backbone of particle identification (PID) at the future Electron Ion Collider (EIC). Currently all the designs for the first EIC detector proposal use a dual Ring Imaging CHerenkov (dRICH) detector in the hadron endcap, a Detector for Internally Reflected Cherenkov (DIRC) light in the barrel, and a modular RICH (mRICH) in the electron endcap. These detectors involve optical processes with many photons that need to be tracked through complex surfaces at the simulation level, while for reconstruction they rely on pattern recognition of ring images. This proceeding summarizes ongoing efforts and possible applications of AI for imaging Cherenkov detectors at EIC. In particular we will provide the example of the dRICH for the AI-assisted design and of the DIRC for simulation and particle identification from complex patterns and discuss possible advantages of using AI.

Research Organization:: Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

DOE Contract Number:: SC0019999

OSTI ID:: 1979438

Journal Information:: Journal of Instrumentation, Journal Name: Journal of Instrumentation Journal Issue: 07 Vol. 17; ISSN 1748-0221

Publisher:: Institute of Physics (IOP)

Country of Publication:: United States

Language:: English

References (12)

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