# The 2nd international conference on particle physics and astrophysics

10-14 October 2016
Milan Hotel
Europe/Moscow timezone

## Identification of low-energy antiprotons on pi-meson background using machine learning methods in PAMELA experiment

11 Oct 2016, 14:15
15m
Vivaldi-Boccerini (Milan Hotel)

### Vivaldi-Boccerini

#### Milan Hotel

Shipilovskaya Street, 28A, Moscow, Russia, 115563
Plenary/section talk Cosmic rays

### Speaker

Anton Lukyanov (PhD student)

### Description

One of main tasks in PAMELA experiment is identification of cosmic ray (CR) antiprotons on different kinds of background. One example of such background at low energies are pi-meson particles which are generated in elements of spectrometer construction by high-energy CR protons. We propose an approach based on machine learning methods, in particular, Support Vector Machines (SVM). We use two different sets of features for classification: track system features (12 measurements of ionization energy losses along particle track) and calorimeter features (different combinations of energy release inside calorimeter along reconstructed particle trajectory). Constructed classifier showed classification accuracy of 96% for antiprotons and 89% for pi-mesons when rigidity $R$ is up to 2 GeV. When $R \in (2, 5]$ classification accuracy for pi-mesons is 15%. For evaluation of classification accuracy we used k-fold cross-validation method with $k=5$.

### Primary author

Anton Lukyanov (PhD student)

### Co-authors

Andrey Mayorov (National Research Nuclear University MEPhI)

### Presentation Materials

 Slides
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