English

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

High Energy Physics - Phenomenology 2020-02-05 v3 High Energy Astrophysical Phenomena Computational Physics

Abstract

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.

Keywords

Cite

@article{arxiv.1907.11846,
  title  = {Hazma: A Python Toolkit for Studying Indirect Detection of Sub-GeV Dark Matter},
  author = {Adam Coogan and Logan Morrison and Stefano Profumo},
  journal= {arXiv preprint arXiv:1907.11846},
  year   = {2020}
}

Comments

Minor revisions; fixed typos in FSR spectra

R2 v1 2026-06-23T10:32:32.243Z