More Evidence for the Redshift Dependence of Color from the JLA Supernova Sample Using Redshift Tomography

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 $\alpha$ and color-luminosity parameter $\beta$. The basic idea is to divide the JLA sample into different redshift bins, assuming that $\alpha$ and $\beta$ are piecewise constants. Then, by constraining the $\Lambda$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 $\beta$ in various subsamples of JLA. Using the full JLA data, we find that $\alpha$ is always consistent with a constant. In contrast, at high redshift $\beta$ has a significant trend of decreasing, at $\sim 3.5\sigma$ confidence level (CL). Moreover, we find that low-$z$ subsample favors a constant $\beta$; in contrast, SDSS and SNLS subsamples favor a decreasing $\beta$ at 2$\sigma$ and $3.3\sigma$ CL, respectively. Besides, by using a binned parameterization of $\beta$, we study the impacts of $\beta$'s evolution on parameter estimation. We find that compared with a constant $\beta$, a varying $\beta$ yields a larger best-fit value of fractional matter density $\Omega_{m0}$, which slightly deviates from the best-fit result given by other cosmological observations. However, for both the varying $\beta$ and the constant $\beta$ cases, the $1\sigma$ regions of $\Omega_{m0}$ are still consistent with the result given by other observations.