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Dark matter constraints from dwarf galaxies: a data-driven LAT analysis

Python code to derive data-driven upper limits on the thermally averaged, velocity-weighted pair-annihilation cross-section (velocity-independent) of a user-defined particle dark matter model using the expected differential gamma-ray spectrum of pair-annihilation events (provided by the user) as ...

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54 commitsLast commit ≈ 42 months ago0 stars1 fork

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Description

Python code to derive data-driven upper limits on the thermally averaged, velocity-weighted pair-annihilation cross-section (velocity-independent) of a user-defined particle dark matter model using the expected differential gamma-ray spectrum of pair-annihilation events (provided by the user) as well as 10 years of Fermi-LAT data from observations of the Milky Way´s dwarf spheroidal galaxies.

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Programming languages
  • Jupyter Notebook 97%
  • Python 3%
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Contributors

FC
Francesca Calore
LAPTh, CNRS
BZ
Bryan Zaldívar
IFT-UAM/CSIC
PS
Pasquale Serpico
LAPTh, CNRS
CE
Christopher Eckner
LAPTh, CNRS

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