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Applying Bayesian neural networks to identify pion, kaon and proton in BES II
Xu, Y; Hou J(侯健); Hou, J; Zhu, KE
2008
发表期刊CHINESE PHYSICS C
卷号32期号:3页码:#REF!
通讯作者Xu, Y (reprint author), Nankai Univ, Dept Phys, Tianjin 300071, Peoples R China.
文章类型Article
摘要The Monte-Carlo samples of pion, kaon and proton generated from 0.3 GeV/c to 1.2 GeV/c by the 'tester' generator from SIMBES which are used to simulate the detector of BES II are identified with the Bayesian neural networks (BNN). The pion identification and misidentification efficiencies are obviously better at high momentum region using BNN than the methods of chi(2) analysis of dE/dX and TOF information. The kaon identification and misidentification efficiencies are obviously better from 0.3 GeV/c to 1.2 GeV/c using BNN than the methods of chi(2) analysis. The proton identification and misidentification efficiencies using BNN axe basically consistent with the ones of chi(2) analysis. The anti-proton identification and misidentification efficiencies are better below 0.6 GeV/c using BNN than the methods of chi(2) analysis.
关键词Bayesian neural networks particle identification pion kaon proton anti-proton
学科领域Physics
收录类别SCI
WOS类目Physics, Nuclear ; Physics, Particles & Fields
WOS记录号WOS:000253748600008
引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ihep.ac.cn/handle/311005/226901
专题实验物理中心
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GB/T 7714
Xu, Y,Hou J,Hou, J,et al. Applying Bayesian neural networks to identify pion, kaon and proton in BES II[J]. CHINESE PHYSICS C,2008,32(3):#REF!.
APA Xu, Y,侯健,Hou, J,&Zhu, KE.(2008).Applying Bayesian neural networks to identify pion, kaon and proton in BES II.CHINESE PHYSICS C,32(3),#REF!.
MLA Xu, Y,et al."Applying Bayesian neural networks to identify pion, kaon and proton in BES II".CHINESE PHYSICS C 32.3(2008):#REF!.
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