Identification of e,μ,π by Neural Network in BES

Zhang Ziping; Chen Hongfang; Ye Shuwei; Zhao Jiawei

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《中国物理C》（英文）编辑部

2024年10月30日

Chinese Physics C> 1997, Vol. 21> Issue(4) : 297-303

Identification of e,μ,π by Neural Network in BES

Department of Modem Physics,University of Science and Technology of China,Hefei 230026

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Abstract：
Two diferent kinds of neural network methods,BP and LVQ,are applied to the identification of e,μ,πparticles in BES experiment,and better results are obtained.The μ data samples used for training and tests are from cosmic events,e and π are strictly selected from real experimental data by very tight cuts.Although their momentum spectrums are non-uniform,interseting enough is that selection efficiencies given by BP test results are quite uniform in the whole momentum range.The results from LVQ is litle worse.It shows that BP is more powerful in pattern recognition than LVQ at least in this study.

References

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Z.J.Jiang,T.J.Wang,Y.G.Xie et al.,Nucl.Inst.and Meth.,A345（1994）541.[2]L.Lnnblad et al.,Nucl.Phys.,B349（1991）675.[3]Wayne S. Babbage,Lee F. Thompson,Nucl.Instr,and Meth.,A330（1993）482.[4]M.Joswig et al.,DESY 93-167,ISSN 0418-9833.[5]张子平、王贻芳，V.Innocente,高能物理与核物理，18（1994）769.[6]A.Cherubini,R.Odorico,Z. Phys.,C53（1992）139.

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Zhang Ziping, Chen Hongfang, Ye Shuwei and Zhao Jiawei. Identification of e,μ,π by Neural Network in BES[J]. Chinese Physics C, 1997, 21(4): 297-303.

Zhang Ziping, Chen Hongfang, Ye Shuwei and Zhao Jiawei. Identification of e,μ,π by Neural Network in BES[J]. Chinese Physics C, 1997, 21(4): 297-303. shu

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Received: 1900-01-01
Revised: 1900-01-01

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1.
沈阳化工大学材料科学与工程学院沈阳 110142

Identification of e,μ,π by Neural Network in BES

Corresponding author: Zhang Ziping,

Department of Modem Physics,University of Science and Technology of China,Hefei 230026

Received Date: 1900-01-01
Accepted Date: 1900-01-01
Available Online: 1997-04-05

Abstract: Two diferent kinds of neural network methods,BP and LVQ,are applied to the identification of e,μ,πparticles in BES experiment,and better results are obtained.The μ data samples used for training and tests are from cosmic events,e and π are strictly selected from real experimental data by very tight cuts.Although their momentum spectrums are non-uniform,interseting enough is that selection efficiencies given by BP test results are quite uniform in the whole momentum range.The results from LVQ is litle worse.It shows that BP is more powerful in pattern recognition than LVQ at least in this study.