Assessment of the Systematic Uncertainties in the Cosmological Analysis of the SDSS Supernovae Photometric Sample
Brodie Popovic, Dan Scolnic, Richard Kessler

TL;DR
This paper re-analyzes the SDSS supernova sample to evaluate systematic uncertainties affecting dark energy measurements, developing new tools and models to improve bias correction accuracy in future large photometric SN surveys.
Contribution
It introduces new analysis methods for host galaxy association, bias correction, and core collapse supernova modeling to better quantify systematic uncertainties in cosmological parameters.
Findings
Mis-association rate of host galaxies is 0.6%.
Bias in w from host galaxy mis-association is +0.0007.
Uncertainty in host galaxy selection efficiency affects w by -0.0072.
Abstract
Improvement in the precision of measurements of cosmological parameters with Type Ia Supernovae (SNIa) is expected to come from large photometrically identified (photometric) SN samples. Here we re-analyse the SDSS photometric SN sample, with roughly 700 high-quality, likely but unconfirmed SNIa light-curves, to develop new analysis tools aimed at evaluating systematic uncertainties on the dark energy equation-of-state parameter . Since we require a spectroscopically measured host galaxy redshift for each SN, we determine the associated selection efficiency of host galaxies in order to simulate bias corrections. We determine that the mis-association rate of host galaxies is ; ignoring this effect in simulated bias corrections leads to a -bias of , where is evaluated from SNIa and priors from measurements of baryon acoustic oscillations and the cosmic…
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