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

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arxiv 2102.05678 v3 pith:BJUUXG25 submitted 2021-02-10 astro-ph.GA astro-ph.CO

classification astro-ph.GAastro-ph.CO
keywords dustpopulationbayesnconsistentfullhostmodelfind
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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    cs.HC 2025-07 conditional novelty 4.0 of 10

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