Constraints on Dark Energy Models Using Late Universe Probes

TL;DR

This study uses multiple late Universe observational probes to constrain dark energy models, finding that the standard $\\Lambda$CDM model remains most favored, with results consistent across various datasets and parameterizations.

Contribution

It provides comprehensive constraints on various dark energy parameterizations using diverse late Universe probes, reaffirming the robustness of the standard $\\Lambda$CDM model.

Findings

$w_0$ and $w_a$ are within 1-2$\sigma$ of $\\Lambda$CDM

$\\Lambda$CDM is the most favored model in Bayesian comparison

DESI BAO LRG data influence the preference for dynamical dark energy

Abstract

We use late Universe probes - Type Ia Supernovae from the PantheonPlus compilation, Quasars, and Dark Energy Spectroscopic Instrument (DESI) Data Release 1 (DR1) BAO data - along with Cosmic Chronometers or Megamasers to constrain various dark energy parameterizations. These include the standard $\Lambda$CDM model ($w_0=-1,w_a=0$), as well as the Chevallier-Polarski-Linder (CPL), Barboza-Alcaniz (BA), Jassal-Bagla-Padmanabhan (JBP), Exponential (EXP), and Transitional Dark Energy (TDE) parameterizations. We find that across all parameterizations, the constrained values of $w_0$ and $w_a$ remain within $(1-2)\sigma$ of the standard $\Lambda$CDM model, irrespective of spatial curvature, dataset combinations, or prior choices. We find from Bayesian model comparison that $\Lambda$CDM remains the most favored model for both flat and non-flat cases, with results remaining robust under different priors. Across all dataset combinations, we reaffirm the fact that LRG1 and LRG2 data points from the DESI BAO dataset are responsible for driving the preference for dynamical dark energy.