| 超高能原初宇宙线成分分辨 |
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| 引用本文： | 冯存峰,孔繁敏,张学尧,何瑁,戴志强,李金玉,张乃健.超高能原初宇宙线成分分辨[J].山东大学学报(理学版),1999,34(4):421-426. |
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| 作者姓名： | 冯存峰 孔繁敏 张学尧 何瑁 戴志强 李金玉 张乃健 |
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| 作者单位： | 山东大学高能物理教研室,济南,250100 |
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| 摘 要： | 根据羊八井AS EC 的实验条件,利用CORSIKA( 版本5 .60) 程序进行了广延大气簇射的Monte Carlo 模拟.通过分析模拟数据,提取与原初成分有关的特征量,并利用人工神经网络对模拟数据进行多参数分析,结果表明,约有85 % 的1015～1017eV 原初质子被羊八井AS EC 正确地挑选出来.
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| 关 键 词： | Monte Carlo模拟 人工神经网络 原初宇宙线分辨 |
| 修稿时间： | 1998-12-29 |
IDENTIFICATION OF PRIMARY COSMIC-RAY COMPONENT AT THE ULTRAHIGH ENERGY REGION |
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| Feng Cunfeng,Kong Fanmin,Zhang Xueyao,He mao,Dai Zhiqiang,Li Jinyu,Zhang Naijian.IDENTIFICATION OF PRIMARY COSMIC-RAY COMPONENT AT THE ULTRAHIGH ENERGY REGION[J].Journal of Shandong University,1999,34(4):421-426. |
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| Authors: | Feng Cunfeng Kong Fanmin Zhang Xueyao He mao Dai Zhiqiang Li Jinyu Zhang Naijian |
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| Abstract: | Based on the observation condition of Yangbaijing experiment, a Monte Carlo simulation for extensive air shower has been done by use of CORSIKA (version5.60) program. The characteristic parameters related to the primary composition are obtained from the simulation results. It is shown that about 85% of the protons can be separated by using the artificial neural networks. |
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| Keywords: | Monte Carlo simulation artificial neural networks identification of primary cosmic-ray component |
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