Particle identification using artificial neural networks at BESIII

Gang Qin; Jun Guang H E Kang Lin Lü; Bian Jian-Ming; C. A O Guo-Fu; Deng Zi-Yan; Miao He; Bin Huang; Xiao Bin Ji; Gang Li; Hai Bo Li; Wei Dong Li; Chun Xiu Liu; Huai Min Liu; Qiu Mei Ma; Xiang Ma; Ya Jun Mao; Ze Pu Mao; Xiao Hu Mo; Jin Fa Qiu; Sheng Sen Sun; Yong Zhao Sun; Ji Ke Wang; Liang Liang Wang; Shuo Pin Wen; Ling Hui Wu; Yu Guang Xie; Zheng Yun You; Ming Yang; Guo Wei Yu; Chang Zheng Yuan; Ye Yuan; Shi Lei Zang; Chang Chun Zhang; Jian Yong Zhang; Ling Zhang; Xue Yao Zhang; Yao Zhang; Yong Sheng Zhu; Jia Heng Zou

doi:10.1088/1674-1137/32/1/001

Particle identification using artificial neural networks at BESIII

Gang Qin, Jun Guang H E Kang Lin Lü, Bian Jian-Ming, C. A O Guo-Fu, Deng Zi-Yan, Miao He, Bin Huang, Xiao Bin Ji, Gang Li, Hai Bo Li, Wei Dong Li, Chun Xiu Liu, Huai Min Liu, Qiu Mei Ma, Xiang Ma, Ya Jun Mao, Ze Pu Mao, Xiao Hu Mo, Jin Fa Qiu, Sheng Sen SunYong Zhao Sun, Ji Ke Wang, Liang Liang Wang, Shuo Pin Wen, Ling Hui Wu, Yu Guang Xie, Zheng Yun You, Ming Yang, Guo Wei Yu, Chang Zheng Yuan, Ye Yuan, Shi Lei Zang, Chang Chun Zhang, Jian Yong Zhang, Ling Zhang, Xue Yao Zhang, Yao Zhang, Yong Sheng Zhu, Jia Heng Zou

Physics and Astronomy (Twin Cities)

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	1-8
Number of pages	8
Journal	Chinese Physics C
Volume	32
Issue number	1
DOIs	https://doi.org/10.1088/1674-1137/32/1/001
State	Published - Jan 2008

Keywords

Artificial neural networks
Multilayered perceptrons
PID variables
Particle identification

Publisher link

10.1088/1674-1137/32/1/001

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Qin, G., Lü, J. G. H. E. K. L., Jian-Ming, B., Guo-Fu, C. A. O., Zi-Yan, D., He, M., Huang, B., Ji, X. B., Li, G., Li, H. B., Li, W. D., Liu, C. X., Liu, H. M., Ma, Q. M., Ma, X., Mao, Y. J., Mao, Z. P., Mo, X. H., Qiu, J. F., ... Zou, J. H. (2008). Particle identification using artificial neural networks at BESIII. Chinese Physics C, 32(1), 1-8. https://doi.org/10.1088/1674-1137/32/1/001

Qin, G, Lü, JGHEKL, Jian-Ming, B, Guo-Fu, CAO, Zi-Yan, D, He, M, Huang, B, Ji, XB, Li, G, Li, HB, Li, WD, Liu, CX, Liu, HM, Ma, QM, Ma, X, Mao, YJ, Mao, ZP, Mo, XH, Qiu, JF, Sun, SS, Sun, YZ, Wang, JK, Wang, LL, Wen, SP, Wu, LH, Xie, YG, You, ZY, Yang, M, Yu, GW, Yuan, CZ, Yuan, Y, Zang, SL, Zhang, CC, Zhang, JY, Zhang, L, Zhang, XY, Zhang, Y, Zhu, YS & Zou, JH 2008, 'Particle identification using artificial neural networks at BESIII', Chinese Physics C, vol. 32, no. 1, pp. 1-8. https://doi.org/10.1088/1674-1137/32/1/001

@article{2176d3c458674a99919cb973cfa5c4cb,

title = "Particle identification using artificial neural networks at BESIII",

abstract = "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.",

keywords = "Artificial neural networks, Multilayered perceptrons, PID variables, Particle identification",

author = "Gang Qin and L{\"u}, \{Jun Guang H E Kang Lin\} and Bian Jian-Ming and Guo-Fu, \{C. A O\} and Deng Zi-Yan and Miao He and Bin Huang and Ji, \{Xiao Bin\} and Gang Li and Li, \{Hai Bo\} and Li, \{Wei Dong\} and Liu, \{Chun Xiu\} and Liu, \{Huai Min\} and Ma, \{Qiu Mei\} and Xiang Ma and Mao, \{Ya Jun\} and Mao, \{Ze Pu\} and Mo, \{Xiao Hu\} and Qiu, \{Jin Fa\} and Sun, \{Sheng Sen\} and Sun, \{Yong Zhao\} and Wang, \{Ji Ke\} and Wang, \{Liang Liang\} and Wen, \{Shuo Pin\} and Wu, \{Ling Hui\} and Xie, \{Yu Guang\} and You, \{Zheng Yun\} and Ming Yang and Yu, \{Guo Wei\} and Yuan, \{Chang Zheng\} and Ye Yuan and Zang, \{Shi Lei\} and Zhang, \{Chang Chun\} and Zhang, \{Jian Yong\} and Ling Zhang and Zhang, \{Xue Yao\} and Yao Zhang and Zhu, \{Yong Sheng\} and Zou, \{Jia Heng\}",

year = "2008",

month = jan,

doi = "10.1088/1674-1137/32/1/001",

language = "English (US)",

volume = "32",

pages = "1--8",

journal = "Chinese Physics C",

issn = "1674-1137",

publisher = "IOP Publishing Ltd.",

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T1 - Particle identification using artificial neural networks at BESIII

AU - Qin, Gang

AU - Lü, Jun Guang H E Kang Lin

AU - Jian-Ming, Bian

AU - Guo-Fu, C. A O

AU - Zi-Yan, Deng

AU - He, Miao

AU - Huang, Bin

AU - Ji, Xiao Bin

AU - Li, Gang

AU - Li, Hai Bo

AU - Li, Wei Dong

AU - Liu, Chun Xiu

AU - Liu, Huai Min

AU - Ma, Qiu Mei

AU - Ma, Xiang

AU - Mao, Ya Jun

AU - Mao, Ze Pu

AU - Mo, Xiao Hu

AU - Qiu, Jin Fa

AU - Sun, Sheng Sen

AU - Sun, Yong Zhao

AU - Wang, Ji Ke

AU - Wang, Liang Liang

AU - Wen, Shuo Pin

AU - Wu, Ling Hui

AU - Xie, Yu Guang

AU - You, Zheng Yun

AU - Yang, Ming

AU - Yu, Guo Wei

AU - Yuan, Chang Zheng

AU - Yuan, Ye

AU - Zang, Shi Lei

AU - Zhang, Chang Chun

AU - Zhang, Jian Yong

AU - Zhang, Ling

AU - Zhang, Xue Yao

AU - Zhang, Yao

AU - Zhu, Yong Sheng

AU - Zou, Jia Heng

PY - 2008/1

Y1 - 2008/1

N2 - 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.

AB - 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.

KW - Artificial neural networks

KW - Multilayered perceptrons

KW - PID variables

KW - Particle identification

UR - https://www.scopus.com/pages/publications/60249086186

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U2 - 10.1088/1674-1137/32/1/001

DO - 10.1088/1674-1137/32/1/001

M3 - Article

AN - SCOPUS:60249086186

SN - 1674-1137

VL - 32

SP - 1

EP - 8

JO - Chinese Physics C

JF - Chinese Physics C

IS - 1

ER -

Particle identification using artificial neural networks at BESIII

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