Malyshev D (2025)
Publication Type: Journal article
Publication year: 2025
Book Volume: 111
Article Number: 043033
Journal Issue: 4
DOI: 10.1103/PhysRevD.111.043033
Excess of gamma rays around the Galactic center (GC) observed in the Fermi Large Area Telescope (LAT) data is one of the most intriguing features in the gamma-ray sky. The spherical morphology and the spectral energy distribution with a peak around a few GeV are consistent with emission from annihilation of dark matter particles. Other possible explanations include a distribution of millisecond pulsars (MSPs). One of the caveats of the MSP hypothesis is the relatively small number of associated MSPs near the GC. In this paper, we perform a multiclass classification of Fermi-LAT sources using machine learning and determine the contribution from unassociated MSP-like sources near the GC. The spectral energy distribution, spatial morphology, and the source count distribution are consistent with expectations for a population of MSPs that can explain the gamma-ray excess. Possible caveats of the contribution from the unassociated MSP-like sources are discussed.
APA:
Malyshev, D. (2025). Towards resolving the Galactic center GeV excess with millisecond-pulsars-like sources using machine learning. Physical Review D, 111(4). https://doi.org/10.1103/PhysRevD.111.043033
MLA:
Malyshev, Dmitry. "Towards resolving the Galactic center GeV excess with millisecond-pulsars-like sources using machine learning." Physical Review D 111.4 (2025).
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