A Bayesian Perspective on Evidence for Evolving Dark Energy

TL;DR

This paper uses Bayesian model comparison to analyze evidence for evolving dark energy, revealing that dataset tensions influence model preference more than direct evidence.

Contribution

It provides a Bayesian perspective on dark energy models, highlighting how dataset tensions affect model selection and emphasizing cautious interpretation of significance.

Findings

Bayesian evidence modestly favors $\\Lambda$CDM with certain data combinations.

Tensions between datasets influence the preference for dynamic dark energy models.

Resolving dataset tensions reduces the Bayesian evidence for evolving dark energy.

Abstract

The DESI Collaboration reports a significant preference for a dynamic dark energy model ($w_0w_a$CDM) over the cosmological constant ($\Lambda$CDM) when their data are combined with other frontier cosmological probes. We present a direct Bayesian model comparison using nested sampling to compute the Bayesian evidence, revealing a contrasting conclusion: for the key combination of the DESI DR2 BAO and the Planck CMB data, we find the Bayesian evidence modestly favours $\Lambda$CDM (log-Bayes factor $\ln B = -0.57{\scriptstyle\pm0.26}$), in contrast to the collaboration's 3.1$\sigma$ frequentist significance in favoring $w_0w_a$CDM. Extending this analysis to also combine with the DES-SN5YR supernova catalogue, our Bayesian analysis reaches a significance of $3.07{\scriptstyle\pm0.10}\,\sigma$ in favour of $w_0w_a$CDM. By performing a comprehensive tension analysis, employing five complementary metrics, we pinpoint the origin: a significant ($2.95{\scriptstyle\pm 0.04}\,\sigma$), low-dimensional tension between DESI DR2 and DES-SN5YR that is present only within the $\Lambda$CDM framework. The $w_0w_a$CDM model is preferred precisely because its additional parameters act to resolve this specific dataset conflict. Replacing DES-SN5YR with the recalibrated DES-Dovekie dataset, this tension is reduced and the three-probe Bayesian evidence for $w_0w_a$CDM vanishes ($\ln B = -0.30{\scriptstyle\pm0.19}$). The convergence of our findings with alternative statistical analyses suggests that the preference for dynamic dark energy is primarily driven by the resolution of inter-dataset tensions, warranting a cautious interpretation of its statistical significance.