The Use of Neural Networks for Classifying Data on the Birth of Elementary Particles in Experiments at the CERN Large Hadron Collider

Student: Kulgildin Bulat

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

Educational Programme: Materials. Devices. Nanotechnology (Master)

Final Grade: 9

Year of Graduation: 2019

In this paper, the problem of reconstruction of particle tracks is studied, the data, which was obtained in computer modeling of particle collision in the synthetic experiment of a CERN and the LHC collaboration, are investigated in. We study the proposed and implemented solutions in the framework of the contest TrackML challenge on the Kaggle platform. An original solution using a neural network is presented, its performance is shown, its limitations are studied. Comparisons are made with several solutions proposed in the framework of the competition.

Full text (added May 19, 2019)

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