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作 者:Zhengyuan Chen Shengsen Sun Huaimin Liu Ziyan Deng Gang Li Shuopin Wen Guang Zhao
机构地区:[1]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2期1264-1271,共8页辐射探测技术与方法(英文)
基 金:supported in part by National Key R&D Program of China under Contracts No.2020YFA0406304.
摘 要:Purpose In the BESIII experiment,a conventional least square method is currently used to calibrate the time-of-flight(TOF)system,aiming to achieve optimal time resolution.However,it is intricate for conventional methods to handle electronics saturation and boundary effect which affect the time resolution.Methods A novel method based on machine learning techniques for time calibration of barrel TOF system is implemented in this paper.Results and conclusion With the application of boosted decision tree(BDT)algorithm,the overall time resolution of barrel TOF is found to be 64 ps.Compared with conventional method,a notable improvement in time resolution is achieved in the boundary range of the scintillator bar using BDT method.
关 键 词:Time calibration Boosted decision trees Time of flight BESIII
分 类 号:O57[理学—粒子物理与原子核物理]
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