mlsanityData to 14 Oct 2026

What Machine Learning Can Do for Focusing Aerogel Detectors

arXiv 2312.02652 ↗First posted 5 Dec 2023hep-ex cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 10 references that are in the map. First posted on arXiv 5 Dec 2023.

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2 of 10 references.

References · 2

  1. 2018Machine Learning in High Energy Physics Community White Papercited by 49
  2. 2020Object condensation: one-stage grid-free multi-object reconstruction in physics detectors, graph and image datacited by 24

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