Particle identification using artificial neural networks at BES

Particle identification using artificial neural networks at BES

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-I...

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Veröffentlicht in:Chinese physics C 2008, Vol.32 (1), p.1-8
1. Verfasser: 秦纲 吕军光 何康林 边渐鸣 曹国富 邓子艳 何苗 黄彬 季晓斌 李刚 李海波 李卫东 刘春秀 刘怀民 马秋梅 马想 冒亚军 毛泽普 莫晓虎 邱进发 孙胜森 孙永昭 王纪科 王亮亮 文硕频 伍灵慧 谢宇广 尤郑昀 杨明 俞国威 苑长征 袁野 臧石磊 张长春 张建勇 张令 张学尧 张瑶 朱永生 印佳恒
Format: Artikel
Sprache:eng
Schlagworte:
人工神经网络技术
模拟技术
物理学
粒子鉴定技术
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Zusammenfassung: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.
ISSN:1674-1137
0254-3052