A Machine Learning classifier for photon selection with the DAMPE detector
August 16, 2017
August 03, 2018
The DArk Matter Particle Explorer (DAMPE) has been successfully launched on the December 17th 2015 and it is able to detect electrons and photons with an unprecedented energy resolution in an energy range going from a few GeV up to 10 TeV. In this work we present a machine learning-based method for photon selection in DAMPE. The selection is based on a classifier which uses the information from the DAMPE sub-detectors, and in particular from the large BGO calorimeter. The classifier was trained on Monte Carlo data and its performance was evaluated. We will also present preliminary results using on orbit data.
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