Improvement in the electron/positron proton separation based on the Electromagnetic Calorimeter of the Alpha Magnetic Spectrometer  

作　　者：Shanglin Li Cheng Zhang Zetong Sun Zhicheng Tang Fengze Zhang Meijun Liang Haotian Yang Yuhang You Hao Chen Hengyi Cai Zixuan Yan Ye Tian Zuhao Li 

机构地区：[1]Key Laboratory of Particle Astrophysics,Institute of High Energy Physics,Chinese Academy of Sciences,Beijing,100049,China [2]University of Chinese Academy of Sciences,Beijing,100049,China

出　　处：《Radiation Detection Technology and Methods》2024年第4期1614-1618,共5页辐射探测技术与方法(英文)

基　　金：supported by National Key R&D Program of China(2022YFA1604802,2022YFA1604803);National Natural Science Foundation of China(11905238);the China Scholarship Council(202204910318).

摘　　要：Background Electron/positron proton separation based on Electromagnetic Calorimeter(ECAL)is crucial for the search for dark matter through precision measurement of cosmic ray positrons for the Alpha Magnetic Spectrometer(AMS-02)experiment.Proton rejection power with Boosted Decision Trees(BDT)technique in existing AMS-02 software decreases in high energy range(beyond 500 GeV),because there are fewer pure proton samples in data as background for BDT training,and proton Monte Carlo(MC)simulation shows disagreement in ECAL energy distribution compared to the data.Purpose Improve the proton rejection power based on ECAL in high energy range.Method Tuning the distribution of the variables of proton MC used in BDT to agree with the proton data.Using proton MC as background training sample with a two-step BDT training approach.Results The proton rejection power above 1.0 TeV is increased to,representing an improvement by a factor of 5 compared to 12×10^(4)the BDT in existing AMS-02 software.

关 键 词：Dark matter Electromagnetic Calorimeter Monte Carlo simulation Electron/positron proton separation Boosted Decision Trees 

分 类 号：O57[理学—粒子物理与原子核物理]