A Localization Method of High Energy Transients for All-sky Gamma-ray Monitor  

作　　者：Yi Zhao Wangchen Xue Shaolin Xiong Qi Luo Yuanhao Wang Jiacong Liu Heng Yu Xiaoyun Zhao Yue Huang Jinyuan Liao Jianchao Sun Xiaobo Li Qibin Yi Ce Cai Shuo Xiao Shenglun Xie Chao Zheng Yanqiu Zhang Chenwei Wang Wenjun Tan Zhiwei Guo Chaoyang Li Zhenghua An Gang Chen Yanqi Du Min Gao Ke Gong Dongya Guo Jiang He Jianjian He Bing Li Gang Li Xinqiao Li Jing Liang Xiaohua Liang Yaqing Liu Xiang Ma Rui Qiao Liming Song Xinying Song Xilei Sun Jin Wang Ping Wang Xiangyang Wen Hong Wu Yanbing Xu Sheng Yang Dali Zhang Fan Zhang Hongmei Zhang Peng Zhang Shu Zhang Zhen Zhang Shijie Zheng Keke Zhang Xingbo Han Haiyan Wu Hu Tai Hao Geng Gaopeng Lu Wei Xu Fanchao Lyu Hongbo Zhang Fangjun Lu Shuangnan Zhang 

机构地区：[1]Department of Astronomy,Beijing Normal University,Beijing 100875,China [2]Key Laboratory of Particle Astrophysics,Institute of High Energy Physics,Chinese Academy of Sciences,Beijing 100049,China [3]University of Chinese Academy of Sciences,Beijing 100049,China [4]School of Physics and Optoelectronics,Xiangtan University,Xiangtan 411105,China [5]College of Physics,Hebei Normal University,Shijiazhuang 050024,China [6]Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing,Guizhou Normal University,Guiyang 550001,China [7]School of Physics and Electronic Science,Guizhou Normal University,Guiyang 550001,China [8]Institute of Astrophysics,Central China Normal University,Wuhan 430079,China [9]College of physics Sciences Technology,Hebei University,Baoding 071002,China [10]Physics and Space Science College,China West Normal University,Nanchong 637002,China [11]School of Computing and Artificial Intelligence,Southwest Jiaotong University,Chengdu 611756,China [12]College of Electronic and information Engineering,Tongji University,Shanghai 201804,China [13]Innovation Academy for Microsatellites of Chinese Academy of Sciences,Shanghai 201304,China [14]National Space Science Center,Chinese Academy of Sciences,Beijing 100190,China [15]School of Earth and Space Sciences,University of Science and Technology of China,Hefei 230026,China [16]Electronic Information School,Wuhan University,Wuhan 430072,China [17]Key Laboratory of Transportation Meteorology of China Meteorological Administration,Nanjing Joint Institute for Atmospheric Sciences,Nanjing 210000,China [18]Key Laboratory of Middle Atmosphere and Global Environment Observation,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China

出　　处：《Research in Astronomy and Astrophysics》2024年第10期25-35,共11页天文和天体物理学研究（英文版）

基　　金：supported by the National Key R&D Program of China(2021YFA0718500);support from the Strategic Priority Research Program on Space Science,the Chinese Academy of Sciences(grant Nos.XDA15360102,XDA15360300,XDA15052700 and E02212A02S);the National Natural Science Foundation of China(grant Nos.12173038 and U2038106);the National HEP Data Center(grant No.E029S2S1)。

摘　　要：Fast and reliable localization of high-energy transients is crucial for characterizing the burst properties and guiding the follow-up observations.Localization based on the relative counts of different detectors has been widely used for all-sky gamma-ray monitors.There are two major methods for this count distribution localization:χ^(2)minimization method and the Bayesian method.Here we propose a modified Bayesian method that could take advantage of both the accuracy of the Bayesian method and the simplicity of the χ^(2)method.With comprehensive simulations,we find that our Bayesian method with Poisson likelihood is generally more applicable for various bursts than the χ^(2)method,especially for weak bursts.We further proposed a location-spectrum iteration approach based on the Bayesian inference,which could alleviate the problems caused by the spectral difference between the burst and location templates.Our method is very suitable for scenarios with limited computation resources or timesensitive applications,such as in-flight localization software,and low-latency localization for rapidly follow-up observations.

关 键 词：methods:data analysis methods:analytical (stars:)gamma-ray burst:general 

分 类 号：P172.3[天文地球—天文学]