More Evidence for the Redshift Dependence of Color from the JLA Supernova Sample Using Redshift Tomography
Miao Li, Nan Li, Shuang Wang, and Lanjun Zhou

TL;DR
This study uses redshift tomography on the JLA supernova sample to investigate the potential redshift dependence of the color-luminosity parameter $eta$, finding significant evolution at high redshift and its impact on cosmological parameter estimates.
Contribution
It introduces a redshift tomography approach to analyze the evolution of supernova parameters, revealing significant high-redshift trends in $eta$ and their effects on cosmological inferences.
Findings
$eta$ decreases significantly at high redshift (~3.5$\sigma$ CL)
Low-$z$ subsample favors constant $eta$
Varying $eta$ affects the estimated $oxed{ ext{matter density}}$ $oxed{ ext{parameter}}$ $ ightarrow$ $oxed{ ext{larger}}$ $oxed{ ext{value}}$
Abstract
In this work, by applying the redshift tomography method to Joint Light-curve Analysis (JLA) supernova sample, we explore the possible redshift-dependence of stretch-luminosity parameter and color-luminosity parameter . The basic idea is to divide the JLA sample into different redshift bins, assuming that and are piecewise constants. Then, by constraining the CDM model, we check the consistency of cosmology-fit results given by the SN sample of each redshift bin. We also adopt the same technique to explore the possible evolution of in various subsamples of JLA. Using the full JLA data, we find that is always consistent with a constant. In contrast, at high redshift has a significant trend of decreasing, at confidence level (CL). Moreover, we find that low- subsample favors a constant ; in…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
