Applications of Machine Learning at BESIII

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 iden...

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Bibliographic Details
Main Authors: Liu Beijiang, Xiong Xian, Hou Guoyi, Song Shiming, Shen Lin
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:EPJ Web of Conferences
Online Access:https://www.epj-conferences.org/articles/epjconf/pdf/2019/19/epjconf_chep2018_06033.pdf
Description
Summary: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.
ISSN:2100-014X