Detection of gamma-ray transients with wild binary segmentation
Sarah Antier, Kateryna Barynova, Piotr Fryzlewicz, Cyril Lachaud,, Gerard Marchal-Duval

TL;DR
This paper introduces FWBSB, an offline method using wild binary segmentation to detect gamma-ray transients in Fermi/GBM data, improving detection of both short and long GRBs and soft X-ray transients.
Contribution
The paper presents a novel application of wild binary segmentation for gamma-ray transient detection, including calibration and performance evaluation on archival data.
Findings
Successfully detects 42 out of 44 onboard GBM events
Identifies additional gamma-ray flares at a rate of 1 per hour
Capable of detecting soft X-ray long transients
Abstract
In the context of time domain astronomy, we present an offline detection search of gamma-ray transients using a wild binary segmentation analysis called FWBSB targeting both short and long gamma-ray bursts (GRBs) and covering the soft and hard gamma-ray bands. We use NASA Fermi/GBM archival data as a training and testing data set. This paper describes the analysis applied to the 12 NaI detectors of the Fermi/GBM instrument. This includes background removal, change-point detection that brackets the peaks of gamma-ray flares, the evaluation of significance for each individual GBM detector and the combination of the results among the detectors. We also explain the calibration of the 10 parameters present in the method using one week of archival data. Finally, we present our detection performance result for 60 days of a blind search analysis with FWBSB by comparing to both the on-board and…
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