Consistency of standard cosmologies using Bayesian model comparison and tension quantification
Lukas Tobias Hergt, Sophie Henrot-Versill\'e, Matthieu Tristram, Douglas Scott

TL;DR
This paper uses Bayesian methods to compare cosmological models and assess data consistency across multiple datasets, finding that recent updates reduce previous tensions and no strong evidence mandates changing the standard LCDM model.
Contribution
It provides a unified Bayesian framework for model comparison and consistency checks in cosmology, incorporating recent data updates and analyzing their impact on model preferences.
Findings
Updated CMB processing improves internal consistency.
Tensions with curvature weaken with recent data.
No robust evidence for evolving dark energy or model change.
Abstract
We present a unified Bayesian assessment of model comparison and data-set consistency for LCDM (cold dark matter plus a cosmological constant) and minimal extensions (neutrino mass, spatial curvature, constant or evolving dark energy) using cosmic microwave background (CMB), baryon acoustic oscillation (BAO), and type Ia supernova (SN) data. The major results are summarized in the first three figures. We quantify model preference with Bayesian evidence and assess consistency with complementary evidence- and likelihood-based diagnostics applied uniformly across data-set combinations. For the models considered, updated Planck processing systematically improves internal CMB consistency (low- versus high-, and primary CMB versus CMB lensing). The preference for a closed geometry and an associated ``curvature tension'' with BAO and/or CMB lensing are largely confined to earlier…
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Taxonomy
TopicsCosmology and Gravitation Theories · Particle physics theoretical and experimental studies · Galaxies: Formation, Evolution, Phenomena
