convenience_functions module

Convenience functions to simulate antiproton fluxes using DRN and calculate likelihoods.

pbarlike.convenience_functions.loglike_recipe(DM_mass, bf, sigma_v, propagation_parameters, prop_model='DIFF.BRK', Data=<class 'pbarlike.data.ams02Data'>, include_low_energy=False, production_xsection_cov=True, prevent_extrapolation=False, verbose=False)

Calculates difference of marginalized chi-squared value between cases of with and without DM.

Parameters:

• DM_mass (int, float, list, or 1D array) – dark matter mass in GeV

• brfr (list or array) – branching fractions to specify the DM annihilation channel; format - [q qbar, c cbar, b bbar, t tbar, W+ W-, Z0 Z0, g g, h h]

• sigma_v (int, float, list or 1D array) – thermally averaged annihilation cross-section in \(cm^3s^{-1}\)

• propagation_parameters (list or array) – propagation parameters (for format and ranges see DRN.load_pp_data()); for marginalization, pass faulty propagation parameters (Eg: [0.])

• propagation_model (str) – “DIFF.BRK” or “INJ.BRK”

• prevent_extrapolation (bool) – decides if DRN should be allowed to predict in parameter regions outside trained region; default-False

• data (1D array) – antiproton flux measurements in :math:(m^2 sr s GeV)^{-1} at energies E; default - 7 year AMS-02 data

• E (1D array) – kinetic energy per nucleon values in GeV at which antiproton measurements are given; default - E_ams

• errors (1D array) – statistical errors at corresponding kinetic energy per nucleon values; default - errors_ams

• data_cov (2D array) – systematic errors at corresponding kinetic energy per nucleon values; default - ams_7y_cov

• xsection_cov (bool) – decides if covariance arising from antiproton production cross-section uncertainties should be included; default - True

• verbose – default - False

Returns:

marginalized chi-squared differences using correlated and uncorrelated errors

Return type:

dictionary