DESI 2024: Reconstructing Dark Energy using Crossing Statistics with DESI DR1 BAO data

TL;DR

This paper uses Crossing Statistics with DESI DR1 BAO data and other cosmological observations to reconstruct the universe's expansion history and dark energy properties in a model-agnostic way, suggesting evolving dark energy behavior.

Contribution

It introduces a novel, model-agnostic approach using Crossing Statistics to analyze dark energy evolution with multiple data sets, extending beyond traditional parametrizations.

Findings

Dark energy appears negligible at redshifts greater than 1.

The cosmological constant is outside 95% confidence intervals in some redshift ranges.

Results are consistent with the $w_0$--$w_a$ dark energy model.

Abstract

We implement Crossing Statistics to reconstruct in a model-agnostic manner the expansion history of the universe and properties of dark energy, using DESI Data Release 1 (DR1) BAO data in combination with one of three different supernova compilations (PantheonPlus, Union3, and DES-SN5YR) and Planck CMB observations. Our results hint towards an evolving and emergent dark energy behaviour, with negligible presence of dark energy at $z\gtrsim 1$, at varying significance depending on the data sets combined. In all these reconstructions, the cosmological constant lies outside the $95\%$ confidence intervals for some redshift ranges. This dark energy behaviour, reconstructed using Crossing Statistics, is in agreement with results from the conventional $w_0$--$w_a$ dark energy equation of state parametrization reported in the DESI Key cosmology paper. Our results add an extensive class of model-agnostic reconstructions with acceptable fits to the data, including models where cosmic acceleration slows down at low redshifts. We also report constraints on $H_0r_d$ from our model-agnostic analysis, independent of the pre-recombination physics.