Abstract
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 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 RV 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 RV = 2.84 ± 0.31 in low-mass hosts, and RV = 2.58 ± 0.23 in high-mass hosts, both consistent with the global value of RV = 2.61 ± 0.21 that we estimate for the full sample. For all choices of mass split we consider, RV 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(RV) = 2.70 ± 0.25 with a 95 per cent upper bound on the population σ(RV) < 0.61. The RV 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.
Highlights
From the landmark discovery of the Universe’s accelerating expansion (Riess et al 1998; Perlmutter et al 1999), to state-of-the-art efforts measuring the Hubble constant (Dhawan et al 2018; Burns et al 2018; Riess et al 2019) and dark energy equation-of-state parameter (Scolnic et al 2018; Abbott et al 2019), Type Ia supernovae (SNe Ia) have been a key pillar in our understanding of cosmology
Mandel et al (2017) showed that the convolution of an intrinsic SN colour-luminosity trend with dust reddening-extinction effects generically results in a nonlinear effective mean apparent colour-luminosity curve, and the conventional linear fit approximates an average of the physically-distinct intrinsic and dust slopes
We have used the light curves of 157 Type Ia supernovae from the first Foundation Supernova Survey data release (Foley et al 2018; Jones et al 2019) to train a B SN SN Ia SED model, continuous over 0.35–0.95 μm
Summary
From the landmark discovery of the Universe’s accelerating expansion (Riess et al 1998; Perlmutter et al 1999), to state-of-the-art efforts measuring the Hubble constant (Dhawan et al 2018; Burns et al 2018; Riess et al 2019) and dark energy equation-of-state parameter (Scolnic et al 2018; Abbott et al 2019), Type Ia supernovae (SNe Ia) have been a key pillar in our understanding of cosmology. We apply the state-of-the-art hierarchical model, B SN (Mandel et al 2020), to analyse current low-redshift data from the Foundation Supernova Survey (Foley et al 2018; Jones et al 2019), and to explore the relation between the dust properties and stellar masses of SN Ia host galaxies. Mandel et al (2017) showed that the convolution of an intrinsic SN colour-luminosity trend with dust reddening-extinction effects generically results in a nonlinear effective mean apparent colour-luminosity curve, and the conventional linear fit approximates an average of the physically-distinct intrinsic and dust slopes It was proposed by Brout & Scolnic (2021) that a difference in the dust properties of low- and high-mass host galaxies is the root cause of the mass step.
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