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基于小波变换的1—10TeV宇宙线周期变化研究
引用本文:刘珺,贾焕玉,黄庆.基于小波变换的1—10TeV宇宙线周期变化研究[J].原子核物理评论,2004,21(1):38-42.
作者姓名:刘珺  贾焕玉  黄庆
作者单位:西南交通大学理学院, 四川 成都 610031
基金项目:西南交通大学基础科学研究基金资助项目
摘    要:利用小波变换, 结合折叠周期分析方法, 对羊八井宇宙线观测站Tibet AS γ阵列1998年4—6月的实验记录数据进行了周期分析, 发现 TeV和10 TeV宇宙线流强观测数据中包含0.5 和1 d周期变化, 其信噪比分别达到10和6. TeV宇宙线0.5 和1 d周期变化的最大变化幅度分别约为0.3%和0.5%, 10 TeV宇宙线约为0.4%和0.7%. We use the technique of wavelet analysis and epoch folding methods to search for the superimposed periodic signals of 1—10 TeV cosmic ray in the data obtained with Tibet Ⅱ/HD AS Array for April to June of 1998. Solar time semi diurnal and diurnal variations have been detected with about signal noise ratio 10 and 6 for the 1 TeV and 10 TeV cosmic ray flux respectively. The semi diurnal variations are of an amplitude 0.3%, a phase 0.9 for 1 TeV cosmic ray and 0.4%, 0.9 for 10 TeV. The diurnal variations are of amplitude 0.5%, 0.7%, and phase 0.8 for 1 TeV and 10 TeV cosmic ray respectively.

关 键 词:宇宙线    周期变化    小波分析
文章编号:1007-4627(2004)01-0038-05
收稿时间:1900-01-01
修稿时间:2003年9月10日

Detection of Superimposed Periodic Variation of 1-10 TeV Cosmic Ray Using Wavelets
LIU Jun,JIA Huan-yu,HUANG Qing.Detection of Superimposed Periodic Variation of 1-10 TeV Cosmic Ray Using Wavelets[J].Nuclear Physics Review,2004,21(1):38-42.
Authors:LIU Jun  JIA Huan-yu  HUANG Qing
Institution:College of Science, Southwest Jiaotong University, Chengdu 610031, China
Abstract:We use the technique of wavelet analysis and epoch folding methods to search for the superimposed periodic signals of 1—10 TeV cosmic ray in the data obtained with Tibet Ⅱ/HD AS Array for April to June of 1998. Solar time semi diurnal and diurnal variations have been detected with about signal noise ratio 10 and 6 for the 1 TeV and 10 TeV cosmic ray flux respectively. The semi diurnal variations are of an amplitude 0.3%, a phase 0.9 for 1 TeV cosmic ray and 0.4%, 0.9 for 10 TeV. The diurnal variations are of amplitude 0.5%, 0.7%, and phase 0.8 for 1 TeV and 10 TeV cosmic ray respectively.
Keywords:cosmic ray  periodic variation  wavelet analysis
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