MadDM v.3.0: a Comprehensive Tool for Dark Matter Studies. (arXiv:1804.00044v2 [hep-ph] UPDATED)
<a href="http://arxiv.org/find/hep-ph/1/au:+Ambrogi_F/0/1/0/all/0/1">Federico Ambrogi</a>, <a href="http://arxiv.org/find/hep-ph/1/au:+Arina_C/0/1/0/all/0/1">Chiara Arina</a>, <a href="http://arxiv.org/find/hep-ph/1/au:+Backovic_M/0/1/0/all/0/1">Mihailo Backovic</a>, <a href="http://arxiv.org/find/hep-ph/1/au:+Heisig_J/0/1/0/all/0/1">Jan Heisig</a>, <a href="http://arxiv.org/find/hep-ph/1/au:+Maltoni_F/0/1/0/all/0/1">Fabio Maltoni</a>, <a href="http://arxiv.org/find/hep-ph/1/au:+Mantani_L/0/1/0/all/0/1">Luca Mantani</a>, <a href="http://arxiv.org/find/hep-ph/1/au:+Mattelaer_O/0/1/0/all/0/1">Olivier Mattelaer</a>, <a href="http://arxiv.org/find/hep-ph/1/au:+Mohlabeng_G/0/1/0/all/0/1">Gopolang Mohlabeng</a>
We present MadDM v.3.0, a numerical tool to compute particle dark matter
observables in generic new physics models. The new version features a
comprehensive and automated framework for dark matter searches at the interface
of collider physics, astrophysics and cosmology and is deployed as a plugin of
the MadGraph5_aMC@NLO platform, inheriting most of its features. With respect
to the previous version, MadDM v.3.0 can now provide predictions for indirect
dark matter signatures in astrophysical environments, such as the annihilation
cross section at present time and the energy spectra of prompt photons, cosmic
rays and neutrinos resulting from dark matter annihilation. MadDM indirect
detection features support both $2to2$ and $2 to n$ dark matter annihilation
processes. In addition, the ability to compare theoretical predictions with
experimental constraints is extended by including the Fermi-LAT likelihood for
gamma-ray constraints from dwarf spheroidal galaxies and by providing an
interface with the nested sampling algorithm PyMultinNest to perform high
dimensional parameter scans efficiently. We validate the code for a wide set of
dark matter models by comparing the results from MadDM v.3.0 to existing tools
and results in the literature.
We present MadDM v.3.0, a numerical tool to compute particle dark matter
observables in generic new physics models. The new version features a
comprehensive and automated framework for dark matter searches at the interface
of collider physics, astrophysics and cosmology and is deployed as a plugin of
the MadGraph5_aMC@NLO platform, inheriting most of its features. With respect
to the previous version, MadDM v.3.0 can now provide predictions for indirect
dark matter signatures in astrophysical environments, such as the annihilation
cross section at present time and the energy spectra of prompt photons, cosmic
rays and neutrinos resulting from dark matter annihilation. MadDM indirect
detection features support both $2to2$ and $2 to n$ dark matter annihilation
processes. In addition, the ability to compare theoretical predictions with
experimental constraints is extended by including the Fermi-LAT likelihood for
gamma-ray constraints from dwarf spheroidal galaxies and by providing an
interface with the nested sampling algorithm PyMultinNest to perform high
dimensional parameter scans efficiently. We validate the code for a wide set of
dark matter models by comparing the results from MadDM v.3.0 to existing tools
and results in the literature.
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