Dynamical Dark Energy in light of DESI BAO and Full-Shape Data

TL;DR

This paper investigates how combining DESI BAO and full-shape matter power spectrum data refines constraints on dynamical dark energy models, providing insights into their viability compared to DM.

Contribution

It introduces a combined likelihood analysis of DESI Y1 data and demonstrates improved constraints on dynamical dark energy parameters.

Findings

Constraints on w0 and wa are tighter with combined data.

DESI Y1 data improves dark energy model parameter bounds.

Analysis supports the sensitivity of full-shape data to dynamical dark energy.

Abstract

Recently, the DESI BAO data has reported a preference of dynamical dark energy (DDE) over the \LambdaCDM cosmology. Apart from the BAO data, the DDE model should be also sensitive to low-redshift measurements of the matter power spectrum data. In this study, we address this point by combining the DESI Y1 data about the matter power spectrum, extracted from the DESI Full-Shape data, with the DESI DR2 BAO data among other probes. After building the DESI Y1 likelihood, we carry out a Markov Chain Monte Carlo analysis, showing that the constraints on $w_0$ and $w_a$ with DESI Y1 data included are improved over those without it for three different datasets widely considered, especially in the case of the DESY5 sample.