Constraining Holographic Dark Energy and Analyzing Cosmological Tensions

TL;DR

This paper constrains holographic dark energy models using multiple cosmological datasets, showing they can reduce tensions in Hubble constant and matter fluctuation amplitude compared to standard models.

Contribution

It provides the first comprehensive analysis of HDE with current datasets, demonstrating its potential to alleviate key cosmological tensions.

Findings

HDE reduces H0 and S8 tensions significantly.

Adding R22 data further tightens constraints on H0 and S8.

HDE fits observational data better than ΛCDM according to AIC and BIC.

Abstract

We investigate cosmological constraints on the holographic dark energy (HDE) using the state-of-the-art cosmological datasets: Planck CMB angular power spectra and weak lensing power spectra, Atacama Cosmology Telescope (ACT) temperature power spectra, baryon acoustic oscillation (BAO) and redshift-space distortion (RSD) measurements from six-degree-field galaxy survey and Sloan Digital Sky Survey (DR12 & DR16) and the Cepheids-Supernovae measurement from SH0ES team (R22). We also examine the HDE model and $\Lambda$CDM with and without $N_{\rm eff}$ (effective number of relativistic species) being treated as a free parameter. We find that the HDE model can relieve the tensions of $H_0$ and $S_8$ to certain degrees. With ``Planck+ACT+BAO+RSD'' datasets, the constraints are $H_0 = 69.70 \pm 1.39\ \mathrm{km\ s^{-1} Mpc^{-1}}$ and $S_8 = 0.823 \pm 0.011$ in HDE model, which brings down the Hubble tension down to $1.92\sigma$ confidence level (C.L.) and the $S_8$ tension to $1$-$2\sigma$ C.L. By adding the R22 data, their values are improved as $H_0 = 71.86 \pm 0.93 \,\mathrm{km\ s^{-1} Mpc^{-1}}$ and $S_8 = 0.813 \pm 0.010$, which further brings the Hubble tension down to $0.85\sigma$ C.L. and relieves the $S_{8}$ tension. We also quantify the goodness-of-fit of different models with Akaike information criterion (AIC) and Bayesian information criterion (BIC), and find that the HDE agrees with the observational data better than the $\Lambda$CDM and other extended models (treating $N_{\rm eff}$ as free for fitting).