A Localization Method of High Energy Transients for All-Sky Gamma-Ray Monitor

TL;DR

This paper introduces a modified Bayesian localization method for high-energy transients in all-sky gamma-ray monitors, improving accuracy for weak bursts and enabling rapid, resource-efficient localization for follow-up observations.

Contribution

A novel Bayesian localization approach that combines the strengths of Bayesian and $ ext{chi}^2$ methods, with an iterative spectrum correction to enhance accuracy.

Findings

Bayesian method outperforms $ ext{chi}^2$ for weak bursts

Proposed method is suitable for real-time, resource-limited scenarios

Spectrum iteration improves localization accuracy

Abstract

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.