Cosmological constraints on generalized Chaplygin gas model: Markov Chain Monte Carlo approach

TL;DR

This study employs Markov Chain Monte Carlo methods to constrain the generalized Chaplygin gas model using diverse observational data, finding results more restrictive than prior studies and indicating a preference for the standard Lambda Cold Dark Matter model.

Contribution

It provides the first comprehensive MCMC-based constraints on the GCG model using combined latest observational data, improving parameter bounds and model comparison.

Findings

GCG model parameters are tightly constrained with current data.

Results favor the standard Lambda CDM model over GCG.

Constraints are more stringent than previous analyses.

Abstract

We use the Markov Chain Monte Carlo method to investigate a global constraints on the generalized Chaplygin gas (GCG) model as the unification of dark matter and dark energy from the latest observational data: the Constitution dataset of type supernovae Ia (SNIa), the observational Hubble data (OHD), the cluster X-ray gas mass fraction, the baryon acoustic oscillation (BAO), and the cosmic microwave background (CMB) data. In a non-flat universe, the constraint results for GCG model are, $\Omega_{b}h^{2}=0.0235^{+0.0021}_{-0.0018}$ ($1\sigma$) $^{+0.0028}_{-0.0022}$ $(2\sigma)$, $\Omega_{k}=0.0035^{+0.0172}_{-0.0182}$ ($1\sigma$) $^{+0.0226}_{-0.0204}$ $(2\sigma)$, $A_{s}=0.753^{+0.037}_{-0.035}$ ($1\sigma$) $^{+0.045}_{-0.044}$ $(2\sigma)$, $\alpha=0.043^{+0.102}_{-0.106}$ ($1\sigma$) $^{+0.134}_{-0.117}$ $(2\sigma)$, and $H_{0}=70.00^{+3.25}_{-2.92}$ ($1\sigma$) $^{+3.77}_{-3.67}$ $(2\sigma)$, which is more stringent than the previous results for constraint on GCG model parameters. Furthermore, according to the information criterion, it seems that the current observations much support $\Lambda$CDM model relative to the GCG model.