Dark energy and cosmic curvature: Monte-Carlo Markov Chain approach

TL;DR

This paper employs Monte-Carlo Markov Chain methods to constrain dark energy properties and cosmic curvature using observational data, achieving tight bounds on curvature and analyzing two dark energy parameterizations.

Contribution

It introduces a MCMC approach to jointly analyze dark energy parameters and cosmic curvature with new observational datasets, providing improved constraints.

Findings

Cosmic curvature constrained to |_k| .03 with one model.

Stronger curvature constraints (_k .02) with the second dark energy model.

Observational data effectively constrains dark energy parameters.

Abstract

We use the Monte-Carlo Markov Chain method to explore the dark energy property and the cosmic curvature by fitting two popular dark energy parameterizations to the observational data. The new 182 gold supernova Ia data and the ESSENCE data both give good constraint on the DE parameters and the cosmic curvature for the dark energy model $w_0+w_a z/(1+z)$. The cosmic curvature is found to be $|\Omega_k|\la 0.03$. For the dark energy model $w_0+w_a z/(1+z)^2$, the ESSENCE data gives better constraint on the cosmic curvature and we get $|\Omega_k|\leq 0.02$.