Research on Identification of μ,π with BESⅢ μ Ιdentifier

YOU Zheng-Yun; MAO Ya-Jun; ZHANG Jia-Wen

Chinese Physics C> 2004, Vol. 28> Issue(9) : 977-981

Research on Identification of μ,π with BESⅢ μ Ιdentifier

Department of Technical Physics,School of Physics,Peking University,Beijing 100871,China2 Institute of High Energy Physics,CAS,Beijing 100039,China

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Abstract：
The final states created by e+e- annihilation at τ-charm energy region are simulated with PYTHIA5.7,and the resultant inclusive muon production cross sections and momentum distributions are obtained.The muon identifier of BESⅢ detector is fully simulated with Geant3.21.For the simulated events containing muons and pions with momentum greater than 0.5GeV/c,the BP neural network and Fisher discriminant method are used for muon/pion identification.BP neural network performs better than Fisher discriminant method.With the same muon efficiency of 96%,the misidentification of pion by BP neural network is 9.4%,in comparison with that of 17.1% by Fisher method.

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YOU Zheng-Yun, MAO Ya-Jun and ZHANG Jia-Wen. Research on Identification of μ,π with BESⅢ μ Ιdentifier[J]. Chinese Physics C, 2004, 28(9): 977-981.

YOU Zheng-Yun, MAO Ya-Jun and ZHANG Jia-Wen. Research on Identification of μ,π with BESⅢ μ Ιdentifier[J]. Chinese Physics C, 2004, 28(9): 977-981. shu

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Received: 2004-01-13
Revised: 1900-01-01

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沈阳化工大学材料科学与工程学院沈阳 110142

Research on Identification of μ,π with BESⅢ μ Ιdentifier

Corresponding author: YOU Zheng-Yun,

Department of Technical Physics,School of Physics,Peking University,Beijing 100871,China2 Institute of High Energy Physics,CAS,Beijing 100039,China

Received Date: 2004-01-13
Accepted Date: 1900-01-01
Available Online: 2004-09-05

Abstract: The final states created by e+e- annihilation at τ-charm energy region are simulated with PYTHIA5.7,and the resultant inclusive muon production cross sections and momentum distributions are obtained.The muon identifier of BESⅢ detector is fully simulated with Geant3.21.For the simulated events containing muons and pions with momentum greater than 0.5GeV/c,the BP neural network and Fisher discriminant method are used for muon/pion identification.BP neural network performs better than Fisher discriminant method.With the same muon efficiency of 96%,the misidentification of pion by BP neural network is 9.4%,in comparison with that of 17.1% by Fisher method.