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[[Eic-projdet-pfrich-l] ] Hybrid machine-learning study for pfRICH PID

From: Charles Joseph Naim <charlesjoseph.naim AT stonybrook.edu>
To: eic-projdet-pfrich-l AT lists.bnl.gov
Subject: [[Eic-projdet-pfrich-l] ] Hybrid machine-learning study for pfRICH PID
Date: Wed, 17 Dec 2025 06:01:01 -0500

Dear all, Please find below a study on a hybrid machine-learning approach for particle identification in the pfRICH detector, based on Cherenkov hit-pattern recognition using a CNN feature extractor combined with gradient-boosted decision trees:

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Dear all,

Please find below a study on a hybrid machine-learning approach for particle identification in the pfRICH detector, based on Cherenkov hit-pattern recognition using a CNN feature extractor combined with gradient-boosted decision trees:

https://arxiv.org/abs/2512.14598

Any comments or suggestions would be very welcome.

Thank you in advance.

Charles

————————————————————————

Dr. Charles-Joseph Naïm

Research associate

Center for Frontiers in Nuclear Science (CFNS)

Stony Brook University
Dept. of Physics and Astronomy
Stony Brook, NY 11794-3800, USA
Office C-117

Phone: +1 347 273 0887

Email: charlesjoseph.naim AT stonybrook.edu

cnaim AT bnl.gov

Zoom ID: 391 825 8156 (pin: 1643)

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[[Eic-projdet-pfrich-l] ] Hybrid machine-learning study for pfRICH PID, Charles Joseph Naim, 12/17/2025