Year: 2023
Type: preprint
Abstract: We describe how a novel online changepoint detection algorithm, called Poisson-FOCuS, can be used to optimally detect gamma-ray bursts within the computational constraints imposed by miniaturized satellites such as the upcoming HERMES-Pathfinder constellation. Poisson-FOCuS enables testing for gamma-ray burst onset at all intervals in a count time series, across all timescales and offsets, in real-time and at a fraction of the computational cost of conventional strategies. We validate an implementation with automatic background assessment through exponential smoothing, using archival data from Fermi-GBM. Through simulations of lightcurves modeled after real short and long gamma-ray bursts, we demonstrate that the same implementation has higher detection power than algorithms designed to emulate the logic of Fermi-GBM and Compton-BATSE, reaching the performances of a brute-force benchmark with oracle information on the true background rate, when not hindered by automatic background assessment. Finally, using simulated data with different lengths and means, we show that Poisson-FOCuS can analyze data twice as fast as a similarly implemented benchmark emulator for the historic Fermi-GBM on-board trigger algorithms.
Source: arXiv (Cornell University)
Institutions: University of Udine, Institute for Space Astrophysics and Planetology, National Institute for Astrophysics, Lancaster University, Istituto Nazionale di Fisica Nucleare, Roma Tor Vergata, Istituto Nazionale di Fisica Nucleare, Sezione di Trieste, Trieste Astronomical Observatory, Institute for Fundamental Physics of the Universe
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Award: G5312053714
OpenAlex ID: W4389820570