Applications of Machine Learning at BESIII
Institute of High Energy Physics, Chinese Academy of Sciences
2 Sichuan University
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Published online: 17 September 2019
BESIII is an experiment at the high precision frontier of hadron physics in τ-charm region. Machine learning techniques have been used to improve the performance of BESIII software. In this proceeding, we present novel approaches with XGBoost for multi-dimensional distribution reweighting, muon identification and cluster reconstruction for CGEM (Cylindrical Gas Electron Multiplier) inner tracker.
© The Authors, published by EDP Sciences, 2019
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