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In this work, by applying the redshift tomography method to Joint Light-curveAnalysis (JLA) supernova sample, we explore the possible redshift-dependence ofstretch-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, byconstraining the $\Lambda$CDM model, we check the consistency of cosmology-fitresults given by the SN sample of each redshift bin. We also adopt the sametechnique to explore the possible evolution of $\beta$ in various subsamples ofJLA. Using the full JLA data, we find that $\alpha$ is always consistent with aconstant. In contrast, at high redshift $\beta$ has a significant trend ofdecreasing, at $\sim 3.5\sigma$ confidence level (CL). Moreover, we find thatlow-$z$ subsample favors a constant $\beta$; in contrast, SDSS and SNLSsubsamples favor a decreasing $\beta$ at 2$\sigma$ and $3.3\sigma$ CL,respectively. Besides, by using a binned parameterization of $\beta$, we studythe impacts of $\beta$'s evolution on parameter estimation. We find thatcompared with a constant $\beta$, a varying $\beta$ yields a larger best-fitvalue of fractional matter density $\Omega_{m0}$, which slightly deviates fromthe best-fit result given by other cosmological observations. However, for boththe varying $\beta$ and the constant $\beta$ cases, the $1\sigma$ regions of$\Omega_{m0}$ are still consistent with the result given by other observations.

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