Abstract
The origin of high-energy galactic cosmic rays is yet to be understood, but some galactic cosmic-ray accelerators can accelerate cosmic rays up to PeV energies. The high-energy cosmic rays are expected to interact with the surrounding material or radiation, resulting in the production of gamma-rays and neutrinos. To optimize for the detection of such associated production of gamma-rays and neutrinos for a given source morphology and spectrum, a multimessenger analysis that combines gamma-rays and neutrinos is required. In this study, we use the MultiMission Maximum Likelihood framework with IceCube Maximum Likelihood Analysis software and HAWC Accelerated Likelihood to search for a correlation between 22 known gamma-ray sources from the third HAWC gamma-ray catalog and 14 yr of IceCube track-like data. No significant neutrino emission from the direction of the HAWC sources was found. We report the best-fit gamma-ray model and 90% CL neutrino flux limit from the 22 sources. From the neutrino flux limit, we conclude that, for five of the sources, the gamma-ray emission observed by HAWC cannot be produced purely from hadronic interactions. We report the limit for the fraction of gamma rays produced by hadronic interactions for these five sources.
Recommended Citation
R. Alfaro et al., "Search For Joint Multimessenger Signals From Potential Galactic Cosmic-Ray Accelerators With HAWC And IceCube," Astrophysical Journal, vol. 976, no. 1, article no. ad812f, American Astronomical Society; IOP Publishing, Nov 2024.
The definitive version is available at https://doi.org/10.3847/1538-4357/ad812f
Department(s)
Physics
Publication Status
Open Access
International Standard Serial Number (ISSN)
1538-4357; 0004-637X
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2025 The Authors, All rights reserved.
Creative Commons Licensing

This work is licensed under a Creative Commons Attribution 4.0 License.
Publication Date
01 Nov 2024

Comments
Australian Research Council, Grant DEC-2017/27/B/ST9/02272