Testing the mutual consistency of different supernovae surveys

TL;DR

This paper introduces a robust statistical test to verify the mutual consistency of different supernova surveys used in cosmology, applying it to major datasets and identifying inconsistencies in one of them.

Contribution

It develops and calibrates a new statistical method for testing the mutual consistency of supernova surveys before joint cosmological analysis.

Findings

No inconsistencies found in the JLA compilation.

Detected inconsistencies in some survey pairs within the UNION2 catalogue.

Provides a tool for validating survey compatibility in cosmological studies.

Abstract

It is now common practice to constrain cosmological parameters using supernovae (SNe) catalogues constructed from several different surveys. Before performing such a joint analysis, however, one should check that parameter constraints derived from the individual SNe surveys that make up the catalogue are mutually consistent. We describe a statistically-robust mutual consistency test, which we calibrate using simulations, and apply it to each pairwise combination of the surveys making up, respectively, the UNION2 catalogue and the very recent JLA compilation by Betoule et al. We find no inconsistencies in the latter case, but conclusive evidence for inconsistency between some survey pairs in the UNION2 catalogue.