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  • 教师拼音名称:Pan Jia
  • 学历:博士研究生毕业
  • 学位:理学博士学位
  • 在职信息:在职
  • 毕业院校:华东师范大学

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Application of Bayesian neural networks to energy reconstruction in EAS experiments for ground-based TeV astrophysics

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所属单位:电子电气与物理学院

发表刊物:Journal of Instrumentation

项目来源:省、自治区、直辖市科技项目

摘要:A toy detector array is designed to detect a shower generated by the interaction between a TeV cosmic ray and the atmosphere. In the present paper, the primary energies of showers detected by the detector array are reconstructed with the algorithm of Bayesian neural networks (BNNs) and a standard method like the LHAASO experiment [1], respectively. Compared to the standard method, the energy resolutions are significantly improved using the BNNs. And the improvement is more obvious for the high energy showers than the low energy ones.

论文类型:期刊论文

论文编号:8432

卷号:11

页面范围:07006

ISSN号:1748-0221

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发表时间:2016-07-12