A shower identification method using a Bayesian statistical model

被引：0

作者：

Kimura, A ^{[1
]}

Shibata, A ^{[1
]}

Takashimizu, N ^{[1
]}

Sasaki, T ^{[1
]}

机构：

[1] Ritsumeikan Univ, Dept Comp Sci, Shiga, Japan

来源：

2003 IEEE NUCLEAR SCIENCE SYMPOSIUM, CONFERENCE RECORD, VOLS 1-5 | 2004年

关键词：

Bayesian network; electromagnetic calorimeter; particle identification;

D O I：

暂无

中图分类号：

TL [原子能技术]; O571 [原子核物理学];

学科分类号：

0827 ; 082701 ;

摘要：

Due to the scale expansion and complexity of experiments in high energy physics experiment, storing data on a database and techniques of knowledge discovery are considered to be useful for efficient storage and analysis of data. We present a new method based on Bayesian statistics to identify electrons and charged pions in shower counters. We designed an ideal shower counter and studied the efficiency using Monte Carlo simulation based on Geant4. Without having any bias, e.g. tracker information, purity of more than 97% have been achieved for identification of both particles.

引用

页码：486 / 489

页数：4

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