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arxiv: 2312.02652 · v2 · pith:V6U3U6FWnew · submitted 2023-12-05 · ✦ hep-ex · cs.LG

What Machine Learning Can Do for Focusing Aerogel Detectors

classification ✦ hep-ex cs.LG
keywords aerogeldetectorfocusinghitslearningmachineparticleambient
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Particle identification at the Super Charm-Tau factory experiment will be provided by a Focusing Aerogel Ring Imaging CHerenkov detector (FARICH). The specifics of detector location make proper cooling difficult, therefore a significant number of ambient background hits are captured. They must be mitigated to reduce the data flow and improve particle velocity resolution. In this work we present several approaches to filtering signal hits, inspired by machine learning techniques from computer vision.

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  1. Performance of the FARICH-based particle identification at charm superfactories using machine learning

    hep-ex 2025-06 unverdicted novelty 4.0

    Simulation study of FARICH-based PID using BDT machine learning classifiers, validated on D0->Kmunu decays showing high pion-muon separation efficiency.