Harvesting BAT-GUANO with NITRATES (Non-Imaging Transient Reconstruction And TEmporal Search): Detecting and localizing the faintest GRBs with a likelihood framework
James DeLaunay, Aaron Tohuvavohu

TL;DR
This paper introduces NITRATES, a likelihood-based framework for detecting and localizing faint GRBs with Swift/BAT data, significantly improving sensitivity over traditional imaging methods and enabling new multi-messenger astrophysics opportunities.
Contribution
The paper develops a maximum likelihood analysis method for BAT data, enhancing sensitivity and localization accuracy for faint GRBs compared to standard coded-mask imaging.
Findings
Boosts GRB detection rate by 3-4 times
Enables localization of some out-of-FOV GRBs
Provides publicly available response functions and code
Abstract
The detection of the gravitational wave counterpart GRB 170817A, underluminous compared to the cosmological GRB population by a factor of 10,000, motivates significant effort in detecting and localizing a dim, nearby, and slightly off-axis population of short GRBs. Swift/BAT is the most sensitive GRB detector in operation, and the only one that regularly localizes GRBs to arcminute precision, critical to rapid followup studies. However, the utility of BAT in targeted sub-threshold searches had been historically curtailed by the unavailability of the necessary raw data for analysis. The new availability of time-tagged event (TTE) data from the GUANO system (arXiv:2005.01751), motivates renewed focus on developing sensitive targeted search analysis techniques to maximally exploit these data. While computationally cheap, we show that the typical coded-mask deconvolution imaging is limited…
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Taxonomy
TopicsChemical and Physical Properties of Materials · Scientific Research and Discoveries · Astro and Planetary Science
