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

Autor: R. Kessler, M. Vincenzi, P. Armstrong
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: The Astrophysical Journal Letters, Vol 952, Iss 1, p L8 (2023)
Druh dokumentu: article
ISSN: 2041-8213
2041-8205
DOI: 10.3847/2041-8213/ace34d
Popis: Bayesian Estimation Applied to Multiple Species (BEAMS) is implemented in the BEAMS with Bias Corrections (BBC) framework to produce a redshift-binned Hubble diagram (HD) for Type Ia supernovae (SNe Ia). BBC corrects for selection effects and non–SN Ia contamination, and systematic uncertainties are described by a covariance matrix with dimension matching the number of BBC redshift bins. For spectroscopically confirmed SN Ia samples, a recent “Binning is Sinning” article showed that an unbinned HD and covariance matrix reduces the systematic uncertainty by a factor of ∼1.5 compared to the binned approach. Here we extend their analysis to obtain an unbinned HD for a photometrically identified sample processed with BBC. To test this new method, we simulate and analyze 50 samples corresponding to the Dark Energy Survey (DES) with a low-redshift anchor; the simulation includes SNe Ia, and contaminants from core-collapse SNe and peculiar SNe Ia. The analysis includes systematic uncertainties for calibration and measures the dark energy equation of state parameter ( w ). Compared to a redshift-binned HD, the unbinned HD with nearly 2000 events results in a smaller systematic uncertainty, in qualitative agreement with BHS21, and averaging results among the 50 samples we find no evidence for a w -bias. To reduce computation time for fitting an unbinned HD with large samples, we propose an HD-rebinning method that defines the HD in bins of redshift, color, and stretch; the rebinned HD results in similar uncertainty as the unbinned case, and shows no evidence for a w -bias.
Databáze: Directory of Open Access Journals
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