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Searching for long faint astronomical high energy transients: a data driven approach

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Searching for long faint astronomical high energy transients: a data driven approach. / Crupi, Riccardo; Dilillo, Giuseppe; Bissaldi, Elisabetta et al.
In: Experimental Astronomy, Vol. 56, 22.11.2023, p. 421-476.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Crupi, R, Dilillo, G, Bissaldi, E, Ward, K, Fiore, F & Vacchi, A 2023, 'Searching for long faint astronomical high energy transients: a data driven approach', Experimental Astronomy, vol. 56, pp. 421-476. https://doi.org/10.1007/s10686-023-09915-7

APA

Crupi, R., Dilillo, G., Bissaldi, E., Ward, K., Fiore, F., & Vacchi, A. (2023). Searching for long faint astronomical high energy transients: a data driven approach. Experimental Astronomy, 56, 421-476. https://doi.org/10.1007/s10686-023-09915-7

Vancouver

Crupi R, Dilillo G, Bissaldi E, Ward K, Fiore F, Vacchi A. Searching for long faint astronomical high energy transients: a data driven approach. Experimental Astronomy. 2023 Nov 22;56:421-476. doi: 10.1007/s10686-023-09915-7

Author

Crupi, Riccardo ; Dilillo, Giuseppe ; Bissaldi, Elisabetta et al. / Searching for long faint astronomical high energy transients : a data driven approach. In: Experimental Astronomy. 2023 ; Vol. 56. pp. 421-476.

Bibtex

@article{d031145cfc874e888b27323737f1c5d0,
title = "Searching for long faint astronomical high energy transients: a data driven approach",
abstract = "HERMES Pathfinder is an in-orbit demonstration consisting of a constellation of six 3U nano-satellites hosting simple but innovative detectors for the monitoring of cosmic high-energy transients. The main objective of HERMES Pathfinder is to prove that accurate position of high-energy cosmic transients can be obtained using miniaturized hardware. The transient position is obtained by studying the delay time of arrival of the signal to different detectors hosted by nano-satellites on low-Earth orbits. In this context, we need to develop novel tools to fully exploit the future scientific data output of HERMES Pathfinder. In this paper, we introduce a new framework to assess the background count rate of a spaceborne, high energy detector; a key step towards the identification of faint astrophysical transients. We employ a neural network to estimate the background lightcurves on different timescales. Subsequently, we employ a fast change-point and anomaly detection technique called Poisson-FOCuS to identify observation segments where statistically significant excesses in the observed count raterelative to the background estimate exist. We test the new software on archival data from the NASA Fermi Gamma-ray Burst Monitor (GBM), which has a collecting area and background level of the same order of magnitude to those of HERMES Pathfinder.The neural network performances are discussed and analyzed over period of both high and low solar activity. We were able to confirm events in the Fermi-GBM catalog, both solar flares and gamma-ray bursts, and found events, not present in Fermi-GBM database, that could be attributed to solar flares, terrestrial gamma-ray flashes, gamma-ray bursts and galactic X-ray flashes. Seven of these are selected and further analyzed, providing an estimate of localisation and a tentative classification.",
keywords = "Gamma-ray burst, Deep learning, Trigger algorithm, Background estimation",
author = "Riccardo Crupi and Giuseppe Dilillo and Elisabetta Bissaldi and Kes Ward and Fabrizio Fiore and Andrea Vacchi",
year = "2023",
month = nov,
day = "22",
doi = "10.1007/s10686-023-09915-7",
language = "English",
volume = "56",
pages = "421--476",
journal = "Experimental Astronomy",
issn = "0922-6435",
publisher = "Springer Netherlands",

}

RIS

TY - JOUR

T1 - Searching for long faint astronomical high energy transients

T2 - a data driven approach

AU - Crupi, Riccardo

AU - Dilillo, Giuseppe

AU - Bissaldi, Elisabetta

AU - Ward, Kes

AU - Fiore, Fabrizio

AU - Vacchi, Andrea

PY - 2023/11/22

Y1 - 2023/11/22

N2 - HERMES Pathfinder is an in-orbit demonstration consisting of a constellation of six 3U nano-satellites hosting simple but innovative detectors for the monitoring of cosmic high-energy transients. The main objective of HERMES Pathfinder is to prove that accurate position of high-energy cosmic transients can be obtained using miniaturized hardware. The transient position is obtained by studying the delay time of arrival of the signal to different detectors hosted by nano-satellites on low-Earth orbits. In this context, we need to develop novel tools to fully exploit the future scientific data output of HERMES Pathfinder. In this paper, we introduce a new framework to assess the background count rate of a spaceborne, high energy detector; a key step towards the identification of faint astrophysical transients. We employ a neural network to estimate the background lightcurves on different timescales. Subsequently, we employ a fast change-point and anomaly detection technique called Poisson-FOCuS to identify observation segments where statistically significant excesses in the observed count raterelative to the background estimate exist. We test the new software on archival data from the NASA Fermi Gamma-ray Burst Monitor (GBM), which has a collecting area and background level of the same order of magnitude to those of HERMES Pathfinder.The neural network performances are discussed and analyzed over period of both high and low solar activity. We were able to confirm events in the Fermi-GBM catalog, both solar flares and gamma-ray bursts, and found events, not present in Fermi-GBM database, that could be attributed to solar flares, terrestrial gamma-ray flashes, gamma-ray bursts and galactic X-ray flashes. Seven of these are selected and further analyzed, providing an estimate of localisation and a tentative classification.

AB - HERMES Pathfinder is an in-orbit demonstration consisting of a constellation of six 3U nano-satellites hosting simple but innovative detectors for the monitoring of cosmic high-energy transients. The main objective of HERMES Pathfinder is to prove that accurate position of high-energy cosmic transients can be obtained using miniaturized hardware. The transient position is obtained by studying the delay time of arrival of the signal to different detectors hosted by nano-satellites on low-Earth orbits. In this context, we need to develop novel tools to fully exploit the future scientific data output of HERMES Pathfinder. In this paper, we introduce a new framework to assess the background count rate of a spaceborne, high energy detector; a key step towards the identification of faint astrophysical transients. We employ a neural network to estimate the background lightcurves on different timescales. Subsequently, we employ a fast change-point and anomaly detection technique called Poisson-FOCuS to identify observation segments where statistically significant excesses in the observed count raterelative to the background estimate exist. We test the new software on archival data from the NASA Fermi Gamma-ray Burst Monitor (GBM), which has a collecting area and background level of the same order of magnitude to those of HERMES Pathfinder.The neural network performances are discussed and analyzed over period of both high and low solar activity. We were able to confirm events in the Fermi-GBM catalog, both solar flares and gamma-ray bursts, and found events, not present in Fermi-GBM database, that could be attributed to solar flares, terrestrial gamma-ray flashes, gamma-ray bursts and galactic X-ray flashes. Seven of these are selected and further analyzed, providing an estimate of localisation and a tentative classification.

KW - Gamma-ray burst

KW - Deep learning

KW - Trigger algorithm

KW - Background estimation

U2 - 10.1007/s10686-023-09915-7

DO - 10.1007/s10686-023-09915-7

M3 - Journal article

VL - 56

SP - 421

EP - 476

JO - Experimental Astronomy

JF - Experimental Astronomy

SN - 0922-6435

ER -