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Identification of new particles from LHC dataset using Machine Learning

By - Subhojit Pal (Department of Physics) and Subhajit Pramanik (Department of Economic Sciences)

 Indian Institute of Science Education and Research (IISER), Bhopal

In this project, we have made a model which will train a classifier to identify the type of a particle, using the datasets of particle collision at LHC. There are mainly five types of particle: electron, proton, muon, kaon, pion. The model is capable of finding some new particle, which is not among the first five or detector noise. Different particle types remain different responses in the detector systems or subdetectors. Thre are five systems: tracking system, Ring imaging Cherenkov detector (RICH), Electromagnetic and Hadron calorimeters, and Muon system. In every level, the particle response differently. The model will identify the type of particles using the responses in the detector systems.

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