Investigating IceCube Neutrino Alerts with the HAWC gamma-Ray Observatory
astro-ph.HE
Submitted: 2026-02-18
Updated: 2026-09-06
Code: https://github.com/threeML/threeML
License: http://creativecommons.org/licenses/by/4.0/
The gist: Neutrino emission from astrophysical sources has long been considered a signature of cosmic-ray acceleration.
Terminology
Abstract
Neutrino emission from astrophysical sources has long been considered a signature of cosmic-ray acceleration. The IceCube neutrino observatory has observed a diffuse flux of TeV-PeV neutrinos, but very few confirmed sources have emerged. With the recent publication of IceCube Event Catalog (IceCat-1), IceCube has released a list of the most promising astrophysical neutrino events since May 2011. Using the archival data from the High Altitude Water Cherenkov (HAWC) Gammma-ray observatory, we perform a coincidence search for gamma rays and neutrinos using a Bayesian Block algorithm with the public IceCube alerts from IceCat-1, along with additional alerts issued later. In this work, we consider 368 alerts, up to July 8, 2025, that are within HAWC's field of view. We observe approximately a 5% coincident detection rate, which is consistent with expectations from background. Two of these detections contain the Active Galactic Nuclei (AGN) Markarian 421 and Markarian 501. We discuss the likelihood that the neutrino/ γ-ray coincidences are false positives and a brief overview of the results.
Sources
- The Southern Wide-Field Gamma-Ray Observatory (SWGO): A Next-Generation Ground-Based Survey Instrument for VHE Gamma-Ray Astronomy
- Longtime Monitoring of TeV Radio Galaxies with HAWC
- HAWC Performance Enhanced by Machine Learning in Gamma-Hadron Separation
- Fermi Large Area Telescope Fourth Source Catalog Data Release 4 (4FGL-DR4)
- The Large High Altitude Air Shower Observatory (LHAASO) Science Book (2021 Edition)
- The Multi-Mission Maximum Likelihood framework (3ML)
- Statistical properties of flux variations in blazar light curves at GeV and TeV energies
- naima: a Python package for inference of relativistic particle energy distributions from observed nonthermal spectra
Related papers
- Numerical Studies of Accretion Flows onto a Neutron Star Engulfed in a Massive Star
- Collisionless Accretion of Finite-Angular-Momentum Plasma onto a Spinning Black Hole
- Impact of Magnetic Field Topology on Electromagnetic and Gravitational Waves from Binary Neutron Star Merger Remnants
- XRISM Resolve Spectroscopy of GX 5-1: Constraints on Iron Spectral Features in a Luminous Neutron-Star Binary
- SN 1006: A Cosmic Laboratory for Investigating Shock Acceleration Physics
- Neutrino Spectral Pinching in 3D Core-Collapse Supernovae: Late-Time Convergence, Failed-Explosion Signatures, and Viewing-Angle Dispersion