DarkRayNet: emulation of cosmic-ray antideuteron fluxes from dark matter

Abstract Cosmic-ray antimatter, particularly low-energy antideuterons, serves as a sensitive probe of dark matter annihilating in our Galaxy. We study this smoking-gun signature and explore its complementarity with indirect dark matter searches using cosmic-ray antiprotons. To this end, we develop the neural network emulator D̅ arkRayNet , enabling a fast prediction of propagated antideuteron energy spectra for a wide range of annihilation channels and their combinations. We revisit the Monte Carlo simulation of antideuteron coalescence and cosmic-ray propagation, allowing us to explore the uncertainties of both processes. In particular, we take into account uncertainties from the Λ b production rate and consider two distinctly different propagation models. Requiring consistency with cosmic-ray antiproton limits, we find that AMS-02 shows sensitivity to a few windows of dark matter masses only, most prominently below 20 GeV. This region can be probed independently by the upcoming GAPS experiment. The program package D̅ arkRayNet is available on GitHub, https://github.com/kathrinnp/DarkRayNet .

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Publication Details

Journal
Journal of Cosmology and Astroparticle Physics
Published
2024-11-01
DOI
https://doi.org/10.1088/1475-7516/2024/11/017
Citations
1
Primary Topic
Dark Matter and Cosmic Phenomena
Type
article
Field-Weighted Citation Impact
0.66
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article

DarkRayNet: emulation of cosmic-ray antideuteron fluxes from dark matter

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1 citations
Journal of Cosmology and Astroparticle Physics
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article

DarkRayNet: emulation of cosmic-ray antideuteron fluxes from dark matter

Kathrin Nippel, Michael Korsmeier, Lena Rathmann, Jan Heisig, Michael Krämer
article en
1 citations

Abstract

Abstract Cosmic-ray antimatter, particularly low-energy antideuterons, serves as a sensitive probe of dark matter annihilating in our Galaxy. We study this smoking-gun signature and explore its complementarity with indirect dark matter searches using cosmic-ray antiprotons. To this end, we develop the neural network emulator D̅ arkRayNet , enabling a fast prediction of propagated antideuteron energy spectra for a wide range of annihilation channels and their combinations. We revisit the Monte Carlo simulation of antideuteron coalescence and cosmic-ray propagation, allowing us to explore the uncertainties of both processes. In particular, we take into account uncertainties from the Λ b production rate and consider two distinctly different propagation models. Requiring consistency with cosmic-ray antiproton limits, we find that AMS-02 shows sensitivity to a few windows of dark matter masses only, most prominently below 20 GeV. This region can be probed independently by the upcoming GAPS experiment. The program package D̅ arkRayNet is available on GitHub, https://github.com/kathrinnp/DarkRayNet .

Journal of Cosmology and Astroparticle PhysicsVol. 2024(11)
Stockholm University (SE), AlbaNova (SE), RWTH Aachen University (DE)
Good health and well-being
Openalex Percentile: Top 14%
Dark Matter and Cosmic Phenomena
0.66
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