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Journal of Instrumentation
Article . 2022 . Peer-reviewed
License: IOP Copyright Policies
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2022
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Artificial Intelligence for imaging Cherenkov detectors at the EIC

Authors: Fanelli, C.; Mahmood, A.;

Artificial Intelligence for imaging Cherenkov detectors at the EIC

Abstract

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.

Keywords

FOS: Computer and information sciences, Physics - Instrumentation and Detectors, Computer Science - Artificial Intelligence, FOS: Physical sciences, Instrumentation and Detectors (physics.ins-det), High Energy Physics - Experiment, High Energy Physics - Experiment (hep-ex), Artificial Intelligence (cs.AI), Nuclear Experiment (nucl-ex), Nuclear Experiment

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green