The role of curvature in the slowing down acceleration scenario

TL;DR

This paper investigates how including curvature as a free parameter affects the consistency of cosmological data sets and the evidence for dark energy evolution at low redshift.

Contribution

It introduces curvature $\Omega_k$ into Bayesian analysis with multiple data sets and examines its impact on data consistency and dark energy evolution.

Findings

Including $\Omega_k$ improves data set consistency

Supports dark energy evolution at low redshift

Reduces tension between different redshift probes

Abstract

We introduce the curvature $\Omega_k$ as a new free parameter in the Bayesian analysis using SNIa, BAO and CMB data, in a model with variable equation of state parameter $w(z)$. We compare the results using both the Constitution and Union 2 data sets, and also study possible low redshift transitions in the deceleration parameter $q(z)$. We found that, incorporating $\Omega_k$ in the analysis, it is possible to make all the three observational probes consistent using both SNIa data sets. Our results support dark energy evolution at small redshift, and show that the tension between small and large redshift probes is ameliorated. However, although the tension decreases, it is still not possible to find a consensus set of parameters that fit all the three data set using the Chevalier-Polarski-Linder CPL parametrization.