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arXiv 2106.03361astro-ph.IMcs.LG
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神经网络在TUS轨道望远镜数据分类中的应用

Application of neural networks to classification of data of the TUS orbital telescope

D.V. Skobeltsyn Institute of Nuclear Physics(D.V.斯科别利岑核物理研究所);M.V. Lomonosov Moscow State University(M.V.罗蒙诺索夫莫斯科国立大学)

Mikhail Zotov

摘要:

我们采用神经网络的TUS荧光望远镜,世界上第一个超高能宇宙射线轨道探测器的数据分类。我们专注于TUS数据中的两种特定类型的信号:由宇宙射线撞击光电探测器产生的轨道状闪光和源自遥远闪电的闪光。我们证明,即使是简单的神经网络与某些传统的数据分析方法相结合,可以非常有效的任务中的荧光望远镜的数据分类。

英文摘要:

We employ neural networks for classification of data of the TUS fluorescence telescope, the world's first orbital detector of ultra-high energy cosmic rays. We focus on two particular types of signals in the TUS data: track-like flashes produced by cosmic ray hits of the photodetector and flashes that originated from distant lightnings. We demonstrate that even simple neural networks combined with certain conventional methods of data analysis can be highly effective in tasks of classification of data of fluorescence telescopes.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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