A machine learning method to separate cosmic ray electrons from protons from 10 to 100 GeV using DAMPE data. (June 2018)

• Record Type: Journal Article
• Authors: Zhao, Hao; Peng, Wen-Xi; Wang, Huan-Yu; Qiao, Rui; Guo, Dong-Ya; Xiao, Hong; Wang, Zhao-Min
• Is Part Of: Research in astronomy and astrophysics. Volume 18:Number 6(2018:Jun.)
• Publication Date: 2018-06
• Subjects: astroparticle physics -- methods: data analysis -- cosmic rays; Astronomy -- Periodicals; Astrophysics -- Periodicals; 520.5
• DOI: 10.1088/1674-4527/18/6/71
• Languages: English
• ISSNs: 1674-4527

Abstract

Abstract: DArk Matter Particle Explorer (DAMPE) is a general purpose high energy cosmic ray and gamma ray observatory, aiming to detect high energy electrons and gammas in the energy range 5 GeV to 10 TeV and hundreds of TeV for nuclei. This paper provides a method using machine learning to identify electrons and separate them from gammas, protons, helium and heavy nuclei with the DAMPE data acquired from 2016 January 1 to 2017 June 30, in the energy range from 10 to 100 GeV.