Machine Learning for Imaging Cherenkov Detectors

• URL: http://arxiv.org/abs/2006.05543v1
• Date: Tue, 9 Jun 2020 22:57:14 GMT
• Title: Machine Learning for Imaging Cherenkov Detectors
• Authors: Cristiano Fanelli
• Abstract summary: This paper focuses on novel directions with applications to Cherenkov detectors. Recent advances on detector design and calibration, as well as particle identification are presented.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Imaging Cherenkov detectors are largely used in modern nuclear and particle physics experiments where cutting-edge solutions are needed to face always more growing computing demands. This is a fertile ground for AI-based approaches and at present we are witnessing the onset of new highly efficient and fast applications. This paper focuses on novel directions with applications to Cherenkov detectors. In particular, recent advances on detector design and calibration, as well as particle identification are presented.

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