An Unsupervised Machine Learning Method for Electron–Proton Discrimination of the DAMPE Experiment
An Unsupervised Machine Learning Method for Electron–Proton Discrimination of the DAMPE Experiment
Galactic cosmic rays are mostly made up of energetic nuclei, with less than $1\%$ of electrons (and positrons). Precise measurement of the electron and positron component requires a very efficient method to reject the nuclei background, mainly protons. In this work, we develop an unsupervised machine learning method to identify …