Applying Bayesian neural networks to identify pion, kaon and proton in BES II

	Applying Bayesian neural networks to identify pion, kaon and proton in BES II
	Xu, Y; Hou J(侯健); Hou, J; Zhu, KE
刊名	CHINESE PHYSICS C
	2008
卷号	32 期号:3 页码:#REF!
关键词	Bayesian neural networks particle identification pion kaon proton anti-proton
通讯作者	Xu, Y (reprint author), Nankai Univ, Dept Phys, Tianjin 300071, Peoples R China.
英文摘要	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.
学科主题	Physics
类目[WOS]	Physics, Nuclear ; Physics, Particles & Fields
收录类别	SCI
WOS记录号	WOS:000253748600008
公开日期	2016-05-03
内容类型	期刊论文
源URL	[http://ir.ihep.ac.cn/handle/311005/226901]
专题	高能物理研究所_实验物理中心
推荐引用方式 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!.