A parametric reconstruction of the deceleration parameter

TL;DR

This paper introduces a new logarithmic parametrization of the deceleration parameter in a flat universe, using observational data to reconstruct the universe's expansion history and compare it with existing models.

Contribution

It proposes a novel logarithmic form for q(z) and constrains its parameters using multiple datasets, enhancing understanding of cosmic acceleration.

Findings

Reconstructed q(z) aligns well with observational data.

Model is consistent with other popular cosmological models.

AIC and BIC criteria favor the proposed parametrization.

Abstract

The present work is based on a parametric reconstruction of the deceleration parameter $q(z)$ in a model for the spatially flat FRW universe filled with dark energy and non-relativistic matter. In cosmology, the parametric reconstruction technique deals with an attempt to build up a model by choosing some specific evolution scenario for a cosmological parameter and then estimate the values of the parameters with the help of different observational datasets. In this paper, we have proposed a logarithmic parametrization of $q(z)$ to probe the evolution history of the universe. Using the type Ia supernova (SNIa), baryon acoustic oscillation (BAO) and the cosmic microwave background (CMB) datasets, the constraints on the arbitrary model parameters $q_{0}$ and $q_{1}$ are obtained (within $1\sigma$ and $2\sigma$ confidence limits) by $\chi^{2}$-minimization technique. We have then reconstructed the deceleration parameter, the total EoS parameter $\omega_{tot}$, the jerk parameter and have compared the reconstructed results of $q(z)$ with other well-known parametrizations of $q(z)$. We have also shown that two model selection criteria (namely, Akaike information criterion and Bayesian Information Criterion) provide the clear indication that our reconstructed model is well consistent with other popular models.