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Activity Number: 546 - Astrostatistics Interest Group: Student Paper Award
Type: Topic Contributed
Date/Time: Thursday, August 11, 2022 : 10:30 AM to 12:20 PM
Sponsor: Astrostatistics Special Interest Group
Abstract #322377
Title: Testing the Consistency of Dust Laws in SN Ia Host Galaxies: A BayeSN Examination of Foundation DR1
Author(s): Stephen Thorp*
Companies: Institute of Astronomy, University of Cambridge
Keywords: astronomy; astrostatistics; supernova; hierarchical Bayes; cosmology; functional data analysis

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 microns, 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. Our Hubble diagram has a low total RMS of 0.13 mag using BayeSN, compared to 0.16 mag using a conventional model (SALT2). We test the consistency of dust laws 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). Modelling population distributions of the dust law R_V in low- and high-mass hosts, we find that both subsamples are highly consistent with the full sample's population mean of 2.70+/-0.25, with a 95% upper bound on the population std. dev. of 0.61. 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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