Measurement of the ultra-rare e K+ → π+ ν ν decay at the NA62 experiment at CERN requires high-performance particle identification to distinguish muons from pions. Calorimetric identification currently in use, based on a boosted decision tree algorithm, achieves a muon misidentification probability of 1.2×10−5 for a pion identification efficiency of 75% in the momentum range of 15–40 GeV/c. In this work, calorimetric identification performance is improved by developing an algorithm based on a convolutional neural network classifier augmented by a filter. Muon misidentification probability is reduced by a factor of six with respect to the current value for a fixed pion-identification efficiency of 75%. Alternatively, pion identification efficiency is improved from 72% to 91% for a fixed muon misidentification probability of 10^−5.

Improved calorimetric particle identification in NA62 using machine learning techniques

Arcidiacono, R.;Boretto, M.;Menichetti, E.;Migliore, E.;Soldi, D.;
2023-01-01

Abstract

Measurement of the ultra-rare e K+ → π+ ν ν decay at the NA62 experiment at CERN requires high-performance particle identification to distinguish muons from pions. Calorimetric identification currently in use, based on a boosted decision tree algorithm, achieves a muon misidentification probability of 1.2×10−5 for a pion identification efficiency of 75% in the momentum range of 15–40 GeV/c. In this work, calorimetric identification performance is improved by developing an algorithm based on a convolutional neural network classifier augmented by a filter. Muon misidentification probability is reduced by a factor of six with respect to the current value for a fixed pion-identification efficiency of 75%. Alternatively, pion identification efficiency is improved from 72% to 91% for a fixed muon misidentification probability of 10^−5.
2023
2023
11
1
15
Cortina Gil, E.; Kleimenova, A.; Minucci, E.; Padolski, S.; Petrov, P.; Shaikhiev, A.; Volpe, R.; Fedorko, W.; Numao, T.; Petrov, Y.; Velghe, B.; Wong...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1954714
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