How Holographic is the Dark Energy? A Spline Nodal reconstruction approach

TL;DR

This paper reconstructs a generalized holographic dark energy model using spline interpolation and Bayesian analysis, showing it fits current cosmological data better than standard models and reducing to LambdaCDM under certain conditions.

Contribution

It introduces a spline-based nodal reconstruction method for holographic dark energy and demonstrates its improved fit to observational data over traditional models.

Findings

Reconstructed HDE model with three nodes fits data better than LambdaCDM.

Standard HDE model is statistically disfavored with a Δχ² of about 20.

The model reduces to LambdaCDM with one node under specific conditions.

Abstract

In this work, we explore the generalized holographic dark energy (HDE) scenario. We relate the HDE density to the future-horizon scale via a function $f(a)$, which we reconstruct via spline-based nodal interpolation. We perform a Bayesian analysis to assess model's consistency with current observations, including baryon acoustic oscillations (BAO) from the Dark Energy Spectroscopic Instrument (DESI) DR1, Type Ia supernovae (SNe Ia) from the Union3 and Pantheon+ compilations, and local measurements of the Hubble constant, $H_0$, from SH0ES. We show that under specific conditions, the model reduces to $\Lambda$CDM with one node. We find strong statistical evidence against the standard HDE model $\Delta \chi^2_{\rm HDE, \; 3\text{-Node}} \sim 20$, and in contrast, the reconstructed HDE model, with three nodes, provides a better fit to the data than the $\Lambda$CDM model, specifically, $\Delta \chi^2_{\Lambda \rm CDM, \; 3\text{-Node}} \sim 12$.