分类： 天文学 >> 天文学 提交时间： 2023-02-19
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
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 counts distribution localization: $\chi^{2}$ 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 $\chi^{2}$ method. With comprehensive simulations, we find that our Bayesian method with Poisson likelihood is generally more applicable for various bursts than $\chi^{2}$ 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 time-sensitive applications, such as in-flight localization software, and low-latency localization for rapid follow-up observations.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
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
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 counts distribution localization: $\chi^{2}$ 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 $\chi^{2}$ method. With comprehensive simulations, we find that our Bayesian method with Poisson likelihood is generally more applicable for various bursts than $\chi^{2}$ 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 time-sensitive applications, such as in-flight localization software, and low-latency localization for rapid follow-up observations.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Peng Zhang
Xiang Ma
Yue Huang
Shaolin Xiong
Shijie Zheng
Liming Song
Ge Ou
Yanqi Du
Jing Liang
Hong Wu
摘要： Background The Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is primarily designed to spot gamma-ray bursts corresponding to gravitational waves. In order to achieve stable observations from various astronomical phenomena, the payload performance need to be monitored during the in-orbit operation. Method This article describes the design and implementation of GECAM satellite payload performance monitoring (GPPM) software. The software extracts the payload status and telescope observations (light curves, energy spectrums, characteristic peak fitting of energy spectrums, etc) from the payload data. Considering the large amount of payload status parameters in the engineering data, we have designed a method of parameter processing based on the configuration tables. This method can deal with the frequent changes of the data formats and facilitate program maintenance. Payload status and performance are monitored through defined thresholds and monitoring reports. The entire software is implemented in python language and the huge amount of observation data is stored in MongoDB. Conclusion The design and implementation of GPPM software have been completed, tested with ground and in-orbit payload data. The software can monitor the performance of GECAM payload effectively. The overall design of the software and the data processing method can be applied to other satellites.
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