Cosmological parameter extraction and biases from type Ia supernova magnitude evolution

TL;DR

This paper investigates how supernova magnitude evolution models impact cosmological parameter estimation, highlighting potential biases and the importance of accounting for evolution in future analyses.

Contribution

It introduces and tests models of supernova magnitude evolution, assessing their effects on cosmological parameter biases using current and simulated future data.

Findings

Data prefer a slight supernova brightness evolution at high redshift.

Neglecting supernova evolution can bias key cosmological parameters, especially the overall mass density.

Late epoch evolution models pose a higher risk of biasing results.

Abstract

We study different one-parametric models of type Ia Supernova magnitude evolution on cosmic time scales. Constraints on cosmological and Supernova evolution parameters are obtained by combined fits on the actual data coming from Supernovae, the cosmic microwave background, and baryonic acoustic oscillations. We find that data prefer a magnitude evolution such that high-redshift Supernova are brighter than would be expected in a standard cosmos with a dark energy component. Data however are consistent with non-evolving magnitudes at the one-sigma level, except special cases. We simulate a future data scenario where SN magnitude evolution is allowed for, and neglect the possibility of such an evolution in the fit. We find the fiducial models for which the wrong model assumption of non-evolving SN magnitude is not detectable, and for which at the same time biases on the fitted cosmological parameters are introduced. Of the cosmological parameters the overall mass density has the strongest chances to be biased due to the wrong model assumption. Whereas early-epoch models with a magnitude offset ~z^2 show up to be not too dangerous when neglected in the fitting procedure, late epoch models with magnitude offset ~sqrt(z) have high chances to bias the fit results.