Particle identification using artificial neural networks at BESⅢ

被引：2

作者：

秦纲 ^{[1
]}

吕军光 ^{[1
]}

何康林 ^{[1
]}

边渐鸣 ^{[1
]}

曹国富 ^{[1
]}

邓子艳 ^{[1
]}

何苗 ^{[1
]}

黄彬 ^{[1
]}

季晓斌 ^{[1
]}

李刚 ^{[1
]}

李海波 ^{[1
]}

李卫东 ^{[1
]}

刘春秀 ^{[1
]}

刘怀民 ^{[1
]}

马秋梅 ^{[1
]}

马想 ^{[1
]}

冒亚军 ^{[2
]}

毛泽普 ^{[1
]}

莫晓虎 ^{[1
]}

邱进发 ^{[1
]}

孙胜森 ^{[1
]}

孙永昭 ^{[1
]}

王纪科 ^{[1
]}

王亮亮 ^{[1
]}

文硕频 ^{[1
]}

伍灵慧 ^{[1
]}

谢宇广 ^{[1
]}

尤郑昀 ^{[2
]}

杨明 ^{[1
]}

俞国威 ^{[1
]}

苑长征 ^{[1
]}

袁野 ^{[1
]}

臧石磊 ^{[1
]}

张长春 ^{[1
]}

张建勇 ^{[1
]}

张令 ^{[3
]}

张学尧 ^{[4
]}

张瑶 ^{[4
]}

朱永生 ^{[1
]}

邹佳恒 ^{[4
]}

机构：

[1] Institute of High Energy Physics CAS

[2] Peking University

[3] Hunan University

[4] Shandong University

来源：

Chinese Physics C | 2008年 / 01期

基金：

中国国家自然科学基金;

关键词：

artificial neural networks; particle identification; PID variables; multilayered perceptrons;

D O I：

暂无

中图分类号：

O572.2 [粒子物理学];

学科分类号：

070202 ;

摘要：

A multilayered perceptrons’ neural network technique has been applied in the particle identification at BESIII.The networks are trained in each sub-detector level.The NN output of sub-detectors can be sent to a sequential network or be constructed as PDFs for a likelihood.Good muon-ID,electron-ID and hadron-ID are obtained from the networks by using the simulated Monte Carlo samples.

引用

页码：1 / 8

页数：8

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