http://arxiv.org/abs/2209.13088
Reliable localization of high-energy transients, such as Gamma-ray Bursts (GRBs) and Soft Gamma-ray Repeaters (SGRs), is the prerequisite for characterizing the burst properties (e.g. spectrum) and implementing the follow-up observations in the multi-wavelength and multi-messenger. Localization based on the relative counts of different detectors has been widely used for all-sky gamma-ray monitors, such as {\it CGRO}/BATSE, {\it Fermi}/GBM, POLAR, and GECAM. There are two major statistical frameworks for counts distribution localization methods: $\chi^{2}$ and Bayesian. Here, we studied and compared several localization methods based on these two statistical frameworks, by directly checking the localization probability map and credible region with comprehensive simulations. We find that the Bayesian method is generally more applicable for various bursts than $\chi^{2}$ method. We also proposed a location-spectrum iteration approach based on the Bayesian inference, which could not only take advantage of straightforward calculation but also alleviate the problems caused by the spectral difference between the burst and location templates.
Y. Zhao, W. Xue, S. Xiong, et. al.
Wed, 28 Sep 22
57/89
Comments: submitted to MNRAS for publication