2021MNRAS.508.4310T

We apply BAYESN, our new hierarchical Bayesian model for the SEDs of Type Ia supernovae (SNe Ia), to analyse the griz light curves of 157 nearby SNe Ia (0.015 < z < 0.08) from the public Foundation Supernova Survey data set. We train a new version of BAYESN, continuous from 0.35 to 0.95 µm, which we use to model the properties of SNe Ia in the rest-frame z-band, study the properties of dust in their host galaxies, and construct a Hubble diagram of SN Ia distances determined from full griz light curves. Our griz Hubble diagram has a low total RMS of 0.13 mag using BAYESN, compared to 0.16 mag using SALT2. Additionally, we test the consistency of the dust law R_V between low- and high-mass host galaxies by using our model to fit the full time- and wavelength-dependent SEDs of SNe Ia up to moderate reddening (peak apparent B - V <= 0.3). Splitting the population at the median host mass, we find R_V = 2.84 ± 0.31 in low-mass hosts, and R_V = 2.58 ± 0.23 in high-mass hosts, both consistent with the global value of R_V = 2.61 ± 0.21 that we estimate for the full sample. For all choices of mass split we consider, R_V is consistent across the step within <= 1.2σ. Modelling population distributions of dust laws in low- and high-mass hosts, we find that both subsamples are highly consistent with the full sample's population mean µ(R_V) = 2.70 ± 0.25 with a 95 per cent upper bound on the population σ(R_V) < 0.61. The R_V population means are consistent within <= 1.2σ. We find that simultaneous fitting of host-mass-dependent dust properties within our hierarchical model does not account for the conventional mass step.