Testing the Consistency of Dust Laws in SN Ia Host Galaxies: A BayeSN Examination of Foundation DR1

TL;DR

This study uses a hierarchical Bayesian model to analyze Type Ia supernovae light curves, examining dust properties in host galaxies and improving distance measurements, with results showing consistent dust laws across different galaxy masses.

Contribution

The paper introduces an enhanced Bayesian model for SN Ia SEDs that simultaneously fits dust properties and improves the accuracy of cosmological distance measurements.

Findings

The $griz$ Hubble diagram has a low RMS of 0.13 mag with BayeSN.

Dust law $R_V$ is consistent across low- and high-mass host galaxies.

Population distributions of dust laws are highly consistent across different host galaxy masses.

Abstract

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 DR1 dataset. We train a new version of BayeSN, continuous from 0.35--0.95 $\mu$m, 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 $B-V \lesssim 0.3$). Splitting the population at the median host mass, we find $R_V=2.84\pm0.31$ in low-mass hosts, and $R_V=2.58\pm0.23$ in high-mass hosts, both consistent with the global value of $R_V=2.61\pm0.21$ that we estimate for the full sample. For all choices of mass split we consider, $R_V$ is consistent across the step within $\lesssim1.2\sigma$. 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 $\mu(R_V) = 2.70\pm0.25$ with a 95% upper bound on the population $\sigma(R_V) < 0.61$. The $R_V$ population means are consistent within $\lesssim1.2\sigma$. We find that simultaneous fitting of host-mass-dependent dust properties within our hierarchical model does not account for the conventional mass step.