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.
翻译:成像切伦科夫探测器是未来电离对撞器(EIC)的粒子识别主干线。目前,首个电离层探测器建议的所有设计都使用黑角端端盖的双环成像 Cherenkov(dRICH) 探测器、桶内内内反射切伦科夫光的探测器以及电子端盖的模块式芯片的红外线探测器。这些探测器涉及光学过程,许多光子需要通过模拟层的复杂表面加以跟踪,而重建则依赖于对环图图的图案识别。该过程总结了人工智能在光学区成像切伦科夫探测器方面正在进行的努力和可能的应用。特别是,我们将举例说明用于人工辅助设计和从复杂模式中模拟和识别粒子的DIRC,并讨论使用AI的可能好处。