Search for neutrinos in coincidence with gravitational wave events from the LIGO-Virgo O3a Observing Run with the Super-Kamiokande detector
The Super-Kamiokande collaboration: K. Abe, C. Bronner, Y. Hayato, M., Ikeda, S. Imaizumi, J. Kameda, Y. Kanemura, Y. Kataoka, S. Miki, M. Miura, S., Moriyama, Y. Nagao, M. Nakahata, S. Nakayama, T. Okada, K. Okamoto, A. Orii,, G. Pronost, H. Sekiya, M. Shiozawa, Y. Sonoda

TL;DR
This study searched for neutrinos coinciding with gravitational wave events from LIGO-Virgo's O3a run using Super-Kamiokande, finding no significant signals but setting limits on neutrino emissions from these sources.
Contribution
It is the first comprehensive search for neutrinos in coincidence with GW events across a wide energy spectrum using Super-Kamiokande, providing constraints on neutrino emissions.
Findings
No significant neutrino excess observed in coincidence with GW events.
Most significant event had a p-value of 7.8%, consistent with background.
Flux limits on neutrino emissions were established for various GW sources.
Abstract
The Super-Kamiokande detector can be used to search for neutrinos in time coincidence with gravitational waves detected by the LIGO-Virgo Collaboration (LVC). Both low-energy ( MeV) and high-energy ( GeV) samples were analyzed in order to cover a very wide neutrino spectrum. Follow-ups of 36 (out of 39) gravitational waves reported in the GWTC-2 catalog were examined; no significant excess above the background was observed, with 10 (24) observed neutrinos compared with 4.8 (25.0) expected events in the high-energy (low-energy) samples. A statistical approach was used to compute the significance of potential coincidences. For each observation, p-values were estimated using neutrino direction and LVC sky map ; the most significant event (GW190602_175927) is associated with a post-trial p-value of (). Additionally, flux limits were computed independently…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
