Data Analysis in Particle Physics by Machine Learning Methods

Student: Sgibnev Ivan

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Materials. Devices. Nanotechnology (Master)

Final Grade: 9

Year of Graduation: 2019

This study is devoted to solving the problem of classifying elementary particles using classical machine learning methods, such as logistic regression, random forest, gradient boosting and deep learning. The purpose of this work is to build a model of the identification of elementary particles, superior to classical methods in quality. In this study a set of models was developed in Python, which implements various methods of machine learning. Using the construction of ensembles of algorithms, the best results were obtained.

Full text (added May 19, 2019)

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