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Searching for very-high-energy electromagnetic counterparts to gravitational-wave events with the Cherenkov Telescope Array

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arxiv 2108.00691 v1 pith:W7D2JKDC submitted 2021-08-02 astro-ph.HE

Barbara Patricelli , Alessandro Carosi , Lara Nava , Monica Seglar-Arroyo , Fabian Schüssler , Antonio Stamerra , Andrea Adelfio , Halim Ashkar
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Andrea Bulgarelli Tristano Di Girolamo Ambra Di Piano Thomas Gasparetto Jarred Green Francesco Longo Ivan Agudo Alessio Berti Elisabetta Bissaldi Giancarlo Cella Antonio Circiello Stefano Covino Giancarlo Ghirlanda Brian Humensky Susumu Inoue Julien Lefaucheur Miroslav Filipovic Massimiliano Razzano Deivid Ribeiro Olga Sergijenko Giulia Stratta Susanna Vergani
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classification astro-ph.HE
keywords grbsdetectioneventsarraycherenkovcounterpartselectromagneticemission
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The detection of electromagnetic (EM) emission following the gravitational wave (GW) event GW170817 opened the era of multi-messenger astronomy with GWs and provided the first direct evidence that at least a fraction of binary neutron star (BNS) mergers are progenitors of short Gamma-Ray Bursts (GRBs). GRBs are also expected to emit very-high energy (VHE, > 100 GeV) photons, as proven by the recent MAGIC and H.E.S.S. observations. One of the challenges for future multi-messenger observations will be the detection of such VHE emission from GRBs in association with GWs. In the next years, the Cherenkov Telescope Array (CTA) will be a key instrument for the EM follow-up of GW events in the VHE range, owing to its unprecedented sensitivity, rapid response, and capability to monitor a large sky area via scan-mode operation. We present the CTA GW follow-up program, with a focus on the searches for short GRBs possibly associated with BNS mergers. We investigate the possible observational strategies and we outline the prospects for the detection of VHE EM counterparts to transient GW events.

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Cited by 1 Pith paper

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  1. Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection

    astro-ph.IM 2025-07 conditional novelty 4.0 of 10

    In simulated GRB detection, quantum fingerprinting encoding consistently outperforms data reuploading, confirming that data encoding choice dominates QML performance.

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