# Artificial Intelligence for Imaging Cherenkov Detectors at the EIC

arXiv: https://arxiv.org/abs/2204.08645 · HTML: https://mlsanity.com/paper/2204.08645/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 23 references that are in the map.
- First posted on arXiv 19 Apr 2022.

## Builds on (most cited first, 6 of 6)

- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [An Introduction to Variational Autoencoders](https://mlsanity.com/paper/1906.02691/) (2019)
- [AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case](https://mlsanity.com/paper/1911.05797/) (2019)
- [DeepRICH: Learning Deeply Cherenkov Detectors](https://mlsanity.com/paper/1911.11717/) (2019)
- [Cherenkov Detectors Fast Simulation Using Neural Networks](https://mlsanity.com/paper/1903.11788/) (2019)
- [Fast Data-Driven Simulation of Cherenkov Detectors Using Generative Adversarial Networks](https://mlsanity.com/paper/1905.11825/) (2019)

## Built on by (most cited first, 1 of 1)

- [Artificial Intelligence for the Electron Ion Collider (AI4EIC)](https://mlsanity.com/paper/2307.08593/) (2023)

## Abstract (arXiv)

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.