Classification of muon tracks from charmonium decays and pion tracks in the model of the SPD detector using neural networks, Классификация мюонных треков от распадов чармония и пионных треков в модели детектора SPD с использованием нейронных сетей

<jats:p>The Machine Learning (ML) approaches were applied to particle identification in the simulation of the Spin Physics Detector (SPD) at the NICA Collider. The results of the identification of muon tracks originating from charmonia decays and pion tracks in the intermediate momenta region (1.5–2.5 GeV/c) are presented. The obtained classifier accuracy is 77% while preserving 99% of muons and rejecting 48% of pions. The efficiency of developed binary classifier is demonstrated through background suppression in J/ψ → µµ decays.</jats:p>