Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Artificial Intelligence for Imaging Cherenkov Detectors at the EIC   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.

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The categories of this paper are: cond-mat
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The categories of this paper are: comp-gas
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The categories of this paper are: supr-con
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The categories of this paper are: gr-qc
33
The categories of this paper are: plasm-ph
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The categories of this paper are: stat
30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
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The categories of this paper are: hep-th
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The categories of this paper are: q-bio
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The categories of this paper are: quant-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: acc-phys
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The categories of this paper are: funct-an
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The categories of this paper are: astro-ph
32
The categories of this paper are: atom-ph