priorMB.nb quickly computes the effective calibration prior on the absolute magnitude M_B of Type Ia supernovae that corresponds to a given determination of H_0. See Camarena & Marra arXiv:1906.11814 and arXiv:2101.08641 for more details.

Have fun, David & Valerio

The latest H_0 determination by SH0ES is (Riess et al. arXiv:2112.04510):
H_0 = 73.04 ± 1.04 km/s/Mpc

The corresponding calibration priors depend on the supernova dataset that one wants to use for the cosmological analysis:

DES-SN3YR dataset (Brout et al 2018) ==> M_B = -19.2432 ± 0.0245 mag

Pantheon dataset (Scolnic et al 2018) ==> M_B = -19.2478 ± 0.0294 mag

Pantheon+ dataset (Scolnic et al 2021) ==> coming...
see github.com/PantheonPlusSH0ES for the CosmoSIS likelihood which includes the full covariance matrix between supernovae and calibrators.

When performing cosmological inference, instead of using the prior on H_0:

,

use the prior on M_B:

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The prior on the supernova absolute magnitude M_B is to be preferred to the prior on H_0 for the following three reasons:
i) one avoids potential double counting of low-redshift supernovae,
ii) one avoids cosmography, in particular fixing the deceleration parameter to the standard model value of q_0=-0.55 (see arXiv:2112.04510 for details),
iii) one includes in the analysis the fact that M_B is constrained by local calibration, an information which would otherwise be neglected in the analysis.

The directory montepython_prior contains the M_B likelihood for Monte Python together with a parameter file example. Monte Python v3.5 already includes this likelihood.

You can use CalPriorSNIa, or part of it, freely, provided that in your publications you acknowledge its use and cite the papers Camarena & Marra arXiv:1906.11814 and arXiv:2101.08641. If using the provided supernova data, please cite the corresponding paper.