Measurement of the ultra-rare K+ -> pi(+)nu(nu) over bar over bar 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 x 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

Cortina Gil, E.;Dalpiaz, P.;Fiorini, M.;Mazzolari, A.;Neri, I.;Norton, A.;Petrucci, F.;Soldani, M.;Wahl, H.;Bandiera, L.;Cotta Ramusino, A.;Gianoli, A.;Romagnoni, M.;Sytov, A.;Iacopini, E.;Latino, G.;Parenti, A.;Georgiev, G.;Lanfranchi, G.;D'Errico, M.;Giordano, R.;Santoni, C.;Barbanera, M.;Pepe, M.;Di Lella, L.;D'Agostini, G.;Turisini, M.;Valente, P.;Vicini, P.;Menichetti, E.;
2023

Abstract

Measurement of the ultra-rare K+ -> pi(+)nu(nu) over bar over bar 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 x 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
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/11392/2565051
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