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Hazma: A Python Toolkit for Studying Indirect Detection of Sub-GeV Dark Matter

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arxiv 1907.11846 v3 pith:KFVWOSDX submitted 2019-07-27 hep-ph astro-ph.HEphysics.comp-ph

classification hep-phastro-ph.HEphysics.comp-ph
keywords darkmatterhazmaspectragamma-rayannihilationcomputingconstraints
verification ladder T0 review T1 audit T2 compute T3 formal
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With several proposed MeV gamma-ray telescopes on the horizon, it is of paramount importance to perform accurate calculations of gamma-ray spectra expected from sub-GeV dark matter annihilation and decay. We present hazma, a python package for reliably computing these spectra, determining the resulting constraints from existing gamma-ray data, and prospects for upcoming telescopes. For high-level analyses, hazma comes with several built-in dark matter models where the interactions between dark matter and hadrons have been determined in detail using chiral perturbation theory. Additionally, hazma provides tools for computing spectra from individual final states with arbitrary numbers of light leptons and mesons, and for analyzing custom dark matter models. hazma can also produce electron and positron spectra from dark matter annihilation, enabling precise derivation of constraints from the cosmic microwave background.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. New bounds on Memory Burdened Primordial Black Holes from Big Bang Nucleosynthesis

    astro-ph.CO 2025-06 reject novelty 4.0 of 10

    Memory-burdened primordial black holes lighter than 10^9 grams are newly constrained by Big Bang nucleosynthesis, with a residual unconstrained window around 1-100 grams for suppression index k=2.

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