Particle identification using artificial neural networks at BESIII

Gang Qin, Jun Guang H E Kang Lin Lü, Bian Jian-Ming, C. A O Guo-Fu, Deng Zi-Yan, Miao He, Bin Huang, Xiao Bin Ji, Gang Li, Hai Bo Li, Wei Dong Li, Chun Xiu Liu, Huai Min Liu, Qiu Mei Ma, Xiang Ma, Ya Jun Mao, Ze Pu Mao, Xiao Hu Mo, Jin Fa Qiu, Sheng Sen SunYong Zhao Sun, Ji Ke Wang, Liang Liang Wang, Shuo Pin Wen, Ling Hui Wu, Yu Guang Xie, Zheng Yun You, Ming Yang, Guo Wei Yu, Chang Zheng Yuan, Ye Yuan, Shi Lei Zang, Chang Chun Zhang, Jian Yong Zhang, Ling Zhang, Xue Yao Zhang, Yao Zhang, Yong Sheng Zhu, Jia Heng Zou

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

A multilayered perceptrons' neural network technique has been applied in the particle identification at BESIII. The networks are trained in each sub-detector level. The NN output of sub-detectors can be sent to a sequential network or be constructed as PDFs for a likelihood. Good muon-ID, electron-ID and hadron-ID are obtained from the networks by using the simulated Monte Carlo samples.

Original languageEnglish (US)
Pages (from-to)1-8
Number of pages8
JournalChinese Physics C
Volume32
Issue number1
DOIs
StatePublished - Jan 2008

Keywords

  • Artificial neural networks
  • Multilayered perceptrons
  • PID variables
  • Particle identification

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