Union Through UNITY: Cosmology with 2,000 SNe Using a Unified Bayesian Framework
David Rubin, Greg Aldering, Marc Betoule, Andy Fruchter, Xiaosheng Huang, Alex G. Kim, Chris Lidman, Eric Linder, Saul Perlmutter, Pilar Ruiz-Lapuente, Nao Suzuki

TL;DR
This paper compiles a large dataset of 2087 Type Ia supernovae, updates light-curve analysis with SALT3, and introduces an improved Bayesian framework, UNITY1.5, to better handle systematic uncertainties and selection effects in cosmological measurements.
Contribution
It presents the Union3 supernova compilation and the UNITY1.5 Bayesian framework, enhancing the analysis of supernova data for cosmology with systematic uncertainty modeling.
Findings
Updated cosmological constraints show tension with LambdaCDM.
Possible evidence for thawing dark energy.
Improved modeling of selection effects and systematics.
Abstract
Type Ia supernovae (SNe Ia) were instrumental in establishing the acceleration of the universe's expansion. By virtue of their combination of distance reach, precision, and prevalence, they continue to provide key cosmological constraints, complementing other cosmological probes. Individual SN surveys cover only over about a factor of two in redshift, so compilations of multiple SN datasets are strongly beneficial. We assemble an up-to-date "Union" compilation of 2087 cosmologically useful SNe Ia from 24 datasets ("Union3"). We take care to put all SNe on the same distance scale and update the light-curve fitting with SALT3 to use the full rest-frame optical. Over the next few years, the number of cosmologically useful SNe Ia will increase by more than a factor of ten, and keeping systematic uncertainties subdominant will be more challenging than ever. We discuss the importance of…
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Taxonomy
TopicsGamma-ray bursts and supernovae
