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The Dark Energy Survey Supernova Program results: Type Ia Supernova brightness correlates with host galaxy dust

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arxiv 2206.06928 v1 pith:36IELMZS submitted 2022-06-14 astro-ph.CO astro-ph.GA

classification astro-ph.COastro-ph.GA
keywords dustsigmahostgalaxiesgalaxyhostsbetafind
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abstract

Cosmological analyses with type Ia supernovae (SNe Ia) often assume a single empirical relation between color and luminosity ($\beta$) and do not account for varying host-galaxy dust properties. However, from studies of dust in large samples of galaxies, it is known that dust attenuation can vary significantly. Here we take advantage of state-of-the-art modeling of galaxy properties to characterize dust parameters (dust attenuation $A_V$, and a parameter describing the dust law slope $R_V$) for the Dark Energy Survey (DES) SN Ia host galaxies using the publicly available \texttt{BAGPIPES} code. Utilizing optical and infrared data of the hosts alone, we find three key aspects of host dust that impact SN Ia cosmology: 1) there exists a large range ($\sim1-6$) of host $R_V$ 2) high stellar mass hosts have $R_V$ on average $\sim0.7$ lower than that of low-mass hosts 3) there is a significant ($>3\sigma$) correlation between the Hubble diagram residuals of red SNe Ia that when corrected for reduces scatter by $\sim13\%$ and the significance of the ``mass step'' to $\sim1\sigma$. These represent independent confirmations of recent predictions based on dust that attempted to explain the puzzling ``mass step'' and intrinsic scatter ($\sigma_{\rm int}$) in SN Ia analyses. We also find that red-sequence galaxies have both lower and more peaked dust law slope distributions on average in comparison to non red-sequence galaxies. We find that the SN Ia $\beta$ and $\sigma_{\rm int}$ both differ by $>3\sigma$ when determined separately for red-sequence galaxy and all other galaxy hosts. The agreement between fitted host-$R_V$ and SN Ia $\beta$ \& $\sigma_{\rm int}$ suggests that host dust properties play a major role in SN Ia color-luminosity standardization and supports the claim that SN Ia intrinsic scatter is driven by $R_V$ variation.

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  1. A Simulation Based Inference Approach to Modelling of Type Ia Supernova Populations

    astro-ph.CO 2026-07 conditional novelty 6.0 of 10

    A simulation-based inference pipeline (Stjörnumál) fits SN Ia dust and intrinsic scatter models to DES 5-year data, enabling fast Bayesian model comparison across seven SN Ia population models.

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