Holographic dark energy in a universe with spatial curvature and massive neutrinos: a full Markov Chain Monte Carlo exploration
Yun-He Li, Shuang Wang, Xiao-Dong Li, Xin Zhang

TL;DR
This study constrains holographic dark energy models with spatial curvature and massive neutrinos using comprehensive observational data and MCMC methods, revealing parameter bounds and degeneracies.
Contribution
It provides the first full MCMC analysis of holographic dark energy with spatial curvature and neutrinos, incorporating perturbation treatment and diverse datasets.
Findings
The parameter c<1 at >4σ for the simplest model.
Spatial curvature increases uncertainties in parameters.
Degeneracy between curvature and neutrino mass enlarges neutrino mass bounds.
Abstract
In this paper, we report the results of constraining the holographic dark energy model with spatial curvature and massive neutrinos, based on a Markov Chain Monte Carlo global fit technique. The cosmic observational data include the full WMAP 7-yr temperature and polarization data, the type Ia supernova data from Union2.1 sample, the baryon acoustic oscillation data from SDSS DR7 and WiggleZ Dark Energy Survey, and the latest measurements of from HST. To deal with the perturbations of dark energy, we adopt the parameterized post-Friedmann method. We find that, for the simplest holographic dark energy model without spatial curvature and massive neutrinos, the phenomenological parameter at more than confidence level. The inclusion of spatial curvature enlarges the error bars and leads to only in about range; in contrast, the inclusion of massive…
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