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Detection of gamma-ray transients with wild binary segmentation

Antier, S, Barynova, K, Fryzlewicz, Piotr ORCID: 0000-0002-9676-902X, Lauchard, C and Marchal-Duval, G (2020) Detection of gamma-ray transients with wild binary segmentation. Monthly Notices of the Royal Astronomical Society, 493 (3). 4428 – 4441. ISSN 0035-8711

[img] Text (Detection of gamma-ray transients with wild binary segmentation) - Accepted Version
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Identification Number: 10.1093/mnras/staa263


In the context of time domain astronomy, we present an offline detection search of gammaray transients using a wild binary segmentation analysis called F-WBSB 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 d of a blind search analysis with F-WBSB by comparing to both the onboard and offline GBM search as well as external events found by others surveys such as Swift-BAT. We detect 42/44 onboard GBM events but also other gamma-ray flares at a rate of 1 per hour in the 4-50 keV band. Our results show that F-WBSB is capable of recovering gamma-ray flares, including the detection of soft X-ray long transients. FWBSB offers an independent identification of GRBs in combination with methods for determining spectral and temporal properties of the transient as well as localization. This is particularly useful for increasing the GRB rate and that will help the joint detection with gravitational-wave events.

Item Type: Article
Official URL:
Additional Information: © 2020 The Authors
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
Q Science > QB Astronomy
Date Deposited: 21 Jan 2020 12:06
Last Modified: 20 Oct 2021 03:29

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