Identification of primary proton component at the  knee with artificial neural networks

CHINESE JOURNAL OF COMPUTATIONAL PHYSICS ›› 1999, Vol. 16 ›› Issue (6): 568-572.

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Identification of primary proton component at the knee with artificial neural networks

Feng Cunfeng, Kong Fanmin, Zhang Xueyao, He Mao, Dai Zhiqiang, Zhang Naijian

High energy physics group, physics department, Shandong University, Jinan 250100

Received:1998-09-29 Revised:1999-05-17 Online:1999-11-25 Published:1999-11-25

Abstract

Abstract: A Monte Carlo simulation for the hybrid experiment of air shower array and emulsion chambers at Yangbajing is done with different interaction models.The feasibility of distinguishing primary cosmic ray components by use of the method of artificial neural netwo rks is studied with the simulation data.T he analysis indicates that the showers induced by primary protons can be efficiently selected by using this method, but the results obtained appear to be dependent on interaction model.The corresponding systematic error is also estimated.

Key words: Monte Carlo simulation, artificial neural networks, identification of primary protons

CLC Number:

Feng Cunfeng, Kong Fanmin, Zhang Xueyao, He Mao, Dai Zhiqiang, Zhang Naijian. Identification of primary proton component at the knee with artificial neural networks[J]. CHINESE JOURNAL OF COMPUTATIONAL PHYSICS, 1999, 16(6): 568-572.

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Identification of primary proton component at the knee with artificial neural networks

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