Machine learning-based lepton identification with the Belle II electromagnetic calorimeter

Sumitted to PubDB: 2022-10-20

Category: Technical Paper, Visibility: Public

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Authors	Torben Ferber, Marcel Hohmann, Peter Krizan, Marco Milesi, Abtin Narimani Charan, Anja Novosel, Luka Santelj, Phillip Urquijo
Date	Oct. 20, 2022
Belle II Number	BELLE2-PUB-TE-2022-001
Abstract	We present a new model for lepton identification with the Belle II electromagnetic calorimeter (ECL). In the central, barrel region, we use energy-weighted CsI(Tl) crystal images in a convolutional neural network architecture to learn energy deposition patterns of electrons, muons and charged hadrons. In the forward and backward angular regions of the ECL, we exploit higher-level observables associated to the lateral energy spread, and per-crystal pulse shape discrimination information in a set of boosted decision trees trained categorically.