Searching for systematics in SNIa and galaxy cluster data using the cosmic duality relation

TL;DR

This paper introduces a model-independent Bayesian method to compare supernova and galaxy cluster data, aiming to detect systematic errors in these cosmological probes without assuming dark energy models.

Contribution

It develops a novel Bayesian Crossing statistic approach to identify inconsistencies between SNIa and galaxy cluster data sets independently of dark energy assumptions.

Findings

Method can detect systematics with high precision

Simulations show effectiveness with future data sets

No assumptions about dark energy are required

Abstract

We compare two different probes of the expansion history of the universe, namely, luminosity distances from type Ia supernovae and angular diameter distances from galaxy clusters, using the Bayesian interpretation of Crossing statistic [1, 2] in conjunction with the assumption of cosmic duality relation. Our analysis is conducted independently of any a-priori assumptions about the nature of dark energy. The model independent method which we invoke searches for inconsistencies between SNIa and galaxy cluster data sets. If detected such an inconsistency would imply the presence of systematics in either of the two data sets. Simulating observations based on expected WFIRST supernovae data and X-ray eROSITA + SZ Planck cluster data, we show that our method allows one to detect systematics with high precision and without advancing any hypothesis about the nature of dark energy.