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

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 in its sensitivity due to several factors. We formalize a maximum likelihood framework for the analysis of BAT data wherein signals are forward modelled through the full instrument response, and -- coupled with the development of new response models -- demonstrate its superior sensitivity to typical imaging via archival comparisons, injection campaigns, and, after implementing as a targeted search, a large number of low-latency GRB discoveries and confirmed arcminute localizations to date. We also demonstrate independent localization of some out-of-FOV GRBs for the first time. NITRATES's increased sensitivity boosts the discovery rate of GRB 170817A-like events in BAT by a factor of at least $3-4$x, along with enabling joint analyses and searches with other GRB, GW, neutrino, and FRB instruments. We provide public access to the response functions and search pipeline code.

Accepted for publication in ApJ. v2 as updated after useful referee feedback. Clarified notation, definition of the test statistic, new figures, better readability. The codebase and instrument responses can be found at https://github.com/Swift-BAT/NITRATES

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Cited by in corpus (4)

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• A search for the afterglows, kilonovae, and host galaxies of two short GRBs: GRB 211106A and GRB 211227A
• ClassiPyGRB: Machine Learning-Based Classification and Visualization of Gamma Ray Bursts using t-SNE
• How Distance Affects GRB Prompt Emission Measurements