Binning is Sinning: Redemption for Hubble Diagram Using Photometrically Classified Type Ia Supernovae

Abstract Bayesian Estimation Applied to Multiple Species (BEAMS) is implemented in the BEAMS with Bias Corrections (BBC) framework produce a redshift-binned Hubble diagram (HD) for Type Ia supernovae (SNe Ia). BBC corrects selection effects and non–SN contamination, systematic uncertainties are described by covariance matrix dimension matching number of redshift bins. For spectroscopically confirmed SN samples, recent “Binning Sinning” article showed that an unbinned HD reduces uncertainty factor ∼1.5 compared binned approach. Here we extend their analysis obtain photometrically identified sample processed BBC. To test this new method, simulate analyze 50 samples corresponding Dark Energy Survey (DES) low-redshift anchor; simulation includes SNe Ia, contaminants from core-collapse peculiar Ia. The calibration measures dark energy equation state parameter ( w ). Compared HD, nearly 2000 events results smaller uncertainty, qualitative agreement BHS21, averaging among find no evidence -bias. reduce computation time fitting large propose HD-rebinning method defines bins redshift, color, stretch; rebinned similar as case, shows