Bayesian analysis of bulk viscous matter dominated universe

Athira Sasidharan,Moncy V John,Titus K Mathew,N D Jerin Mohan

doi:10.1140/epjc/s10052-018-6105-5

Abstract

In our previous works, we have analyzed the evolution of bulk viscous matter dominated universe with a more general form for bulk viscous coefficient, zeta =zeta _{0}+zeta _{1}frac{dot{a}}{a}+zeta _{2}frac{ddot{a}}{dot{a}} and also carried out the dynamical system analysis. We found that the model reasonably describes the evolution of the universe if the viscous coefficient is a constant. In the present work we are contrasting this model with the standard varLambda CDM model of the universe using the Bayesian method. We have shown that, even though the viscous model gives a reasonable back ground evolution of the universe, the Bayes factor of the model indicates that, it is not so superior over the varLambda CDM model, but have a slight advantage over it.

Highlights

As in the case of the Chaplygin gas model, another possibility of the unified description of both dark energy and dark matter arises in the dissipative fluid models
Later these authors [36] extended their model by taking varying bulk viscosity of the form ζ = ζ0 + ζ1 H and found that it shows a background evolution close to that of the standard ΛCDM model
In some earlier works we have shown that this class of models reasonably explained the background evolution of the universe

Summary

Introduction

As in the case of the Chaplygin gas model, another possibility of the unified description of both dark energy and dark matter arises in the dissipative fluid models. In [33], by considering a single cosmic component, which is the dark matter with bulk viscosity, ζ (ρ) = αρm with α and m being constants, the authors have shown that, the universe can make a transition from a decelerating phase to a late accelerating phase and to a de Sitter epoch. Inspite of this good background evolution, the model have come across with some negative aspects while analysing the structure formation. Let Mi and M j be the two models which we need to compare, using Bayes theorem the ratio between their posterior probability

Bayesian model comparison

Bulk viscous FLRW Universe

Bayesian analysis of bulk viscous models

Findings

Conclusion