The Pantheon+ Analysis: Forward-Modeling the Dust and Intrinsic Colour Distributions of Type Ia Supernovae, and Quantifying their Impact on Cosmological Inferences

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Popovic, Brodie

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Brout, Dillon

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Kessler, Richard

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Scolnic, Daniel

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2021-12-25T14:53:58Z

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2021-12-25T14:53:58Z

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2021-12-25T14:53:57Z

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Recent studies have shown that the observed colour distributions of Type Ia SNe (SNIa) are well-described by a combination of distributions from dust and intrinsic colour. Here we present a new forward-modeling fitting method (Dust2Dust) to measure the parent dust and colour distributions, including their dependence on host-galaxy mass. At each fit step, the SNIa selection efficiency is determined from a large simulated sample that is re-weighted to reflect the proposed distributions. We use five separate metrics to constrain the Dust2Dust parameters: distribution of fitted light-curve colour $c$, cosmological residual trends with $c$, cosmological residual scatter with $c$, fitted colour-luminosity relationship $\beta_{\rm SALT2}$, and intrinsic scatter $\sigma_{\rm int}$. Using the Pantheon+ data sample, we present results for a Dust2Dust fit that includes 4 parameters describing intrinsic colour variations and 8 parameters describing dust. Furthermore, we propagate the Dust2Dust parameter uncertainties and covariance to the dark energy equation-of-state $w$ and Hubble constant H$0$: we find $\sigma_w = 0.005$ and $\sigma{\textrm{H}_0} = 0.145~$km/s/Mpc. The Dust2Dust code is publically available.

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https://hdl.handle.net/10161/24134

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astro-ph.CO

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astro-ph.CO

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astro-ph.GA

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The Pantheon+ Analysis: Forward-Modeling the Dust and Intrinsic Colour Distributions of Type Ia Supernovae, and Quantifying their Impact on Cosmological Inferences

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Journal article

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Scolnic, Daniel|0000-0002-4934-5849

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Trinity College of Arts & Sciences

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Physics

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Duke

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