Gamma-Ray Burst Detection with Poisson-FOCuS and Other Trigger Algorithms

Dilillo, Giuseppe and Ward, Kes and Eckley, Idris A. and Fearnhead, Paul and Crupi, Riccardo and Evangelista, Yuri and Vacchi, Andrea and Fiore, Fabrizio (2024) Gamma-Ray Burst Detection with Poisson-FOCuS and Other Trigger Algorithms. The Astrophysical Journal, 962 (2): 137. ISSN 0004-637X

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Abstract

We describe how a novel online change-point 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 performance 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.

Item Type:
Journal Article
Journal or Publication Title:
The Astrophysical Journal
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/3100/3103
Subjects:
?? transient detectionalgorithmsartificial satellitesastrostatistics techniquesgamma-ray burstsastronomy and astrophysicsspace and planetary science ??
ID Code:
214751
Deposited By:
Deposited On:
16 Feb 2024 11:05
Refereed?:
Yes
Published?:
Published
Last Modified:
16 Jul 2024 00:54