多参量分析法在γ射线与强子分辨中的应用  

Application of Mutti-variant Analysis in Separating the γ-initiated and Hadron-initiated Showers

作　　者：赵荣霞[1] 李爱萍[1] 

机构地区：[1]滨州学院物理与电子科学系,山东滨州256603

出　　处：《滨州学院学报》2010年第3期58-61,共4页Journal of Binzhou University

摘　　要：利用TMVA软件包所提供人工神经网络方法进行了多参量的分析,实现对γ射线和强子簇射的分辨.测试结果表明,在对强子簇射的排斥率达到75%的条件下,对γ射线簇射的挑选率可达到80%以上,最高品质因子为2.06.Multi-variant analysis is performed with TMVA（Toolkit for Multivariate Analysis）program to separate the γ-initiated and hadron-initiated showers.The test shows that the efficiency for selecting the γ-initiated showers can reach more than 80% while rejecting more than 75% of the hadron-initiated showers.The best quality factor is 2.06.

关 键 词：甚高能 广延大气簇射 特征量 品质因子 人工神经网络 

分 类 号：O572.1[理学—粒子物理与原子核物理]