Diagnostics and future evolution analysis of the two parametric models

TL;DR

This paper evaluates two parametric models of effective pressure using diagnostics like $Om$, Statefinder hierarchy, and growth rate, comparing them with the $ ext{Lambda}$CDM model to distinguish their behaviors and future evolution.

Contribution

The study applies multiple diagnostics to effectively differentiate two parametric models from $ ext{Lambda}$CDM and from each other, providing insights into their future universe evolution.

Findings

$Om$ diagnostic shows models are similar to $ ext{Lambda}$CDM at 68% confidence.

Statefinder hierarchy and growth rate diagnostics distinguish models from $ ext{Lambda}$CDM.

Models can be differentiated from each other more clearly with advanced diagnostics.

Abstract

In this paper, we apply three diagnostics including $Om$, Statefinder hierarchy and the growth rate of perturbations into discriminating the two parametric models for the effective pressure with the $\Lambda$CDM model. By using the $Om$ diagnostic, we find that both the model 1 and the model 2 can be hardly distinguished from each other as well as the $\Lambda$CDM model in terms of 68\% confidence level. As a supplement, by using the Statefinder hierarchy diagnostics and the growth rate of perturbations, we discover that not only can our two parametric models be well distinguished from $\Lambda$CDM model, but also, by comparing with $Om$ diagnostic, the model 1 and the model 2 can be distinguished better from each other. In addition, we also explore the fate of universe evolution of our two models by means of the rip analysis.