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Publication

Imaging particle collision data for event classification using machine learning

Authors

Chekanov, Sergei

Abstract

We propose a method to organize experimental data from particle collision experiments in a general format which can enable a simple visualisation and effective classification of collision data using machine learning techniques. The method is based on sparse fixed-size matrices with single- and two-particle variables containing information on identified particles and jets. We illustrate this method using an example of searches for new physics at the LHC experiments.

Division

HEP

Publication Year

2019

Publication Type

Article

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