BESⅢμ子鉴别器μ,π鉴别的研究  

Research on Identification of μ,π with BESⅢ μ Ιdentifier

作　　者：尤郑昀[1] 冒亚军[1] 张家文[2] 

机构地区：[1]北京大学物理学院技术物理系,北京100871 [2]中国科学院高能物理研究所,北京100039

出　　处：《高能物理与核物理》2004年第9期977-981,共5页High Energy Physics and Nuclear Physics

基　　金：国家自然科学基金 ( 10 3 75 0 0 2 )资助~~

摘　　要：用事件产生软件PYTHIA模拟了τ粲能区正负电子对撞的各反应道 ,得到各反应道产生末态 μ子的截面和动量分布 .用模拟软件Geant3对BESⅢ的 μ子鉴别器进行了模拟 .对动量为0 .5GeV/c以上的 μ子和π介子的模拟数据 ,用BP神经网络方法和Fisher判别方法进行 μ ,π鉴别 .BP神经网络具有非线性的模式识别能力 ,其 μ 。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.

关 键 词：高能物理实验 粒子鉴别 神经网络法 Geant3软件 μ子鉴别器 Π介子 北京谱仪实验 

分 类 号：O572.323[理学—粒子物理与原子核物理]