Red-shift parametrizations of dark energy and observational constraint on their parameters: Galileon gravity as background

TL;DR

This study investigates four dark energy models with different EoS parametrizations within Galileon gravity, constraining their parameters using observational data and comparing their predictions with supernova data.

Contribution

It introduces and constrains four dark energy parametrizations in Galileon gravity, analyzing their compatibility with observational data and highlighting the limitations of the logarithmic model.

Findings

Best-fit parameters obtained at various confidence levels.

Logarithmic model parameters could not be finitely constrained.

SNe Type Ia 292 data favors the models at low redshifts.

Abstract

In this work, FRW universe filled with dark matter (perfect fluid with negligible pressure) along with dark energy in the background of Galileon gravity is considered. Four dark energy models with different EoS parametrizations have been employed namely, Linear, CPL, JBP and Logarithmic parametrizations. From Stern, Stern+BAO and Stern+BAO+CMB joint data analysis, we have obtained the bounds of the arbitrary parameters $\omega_{0}$ and $\omega_{1}$ by minimizing the $\chi^{2}$ test. The best-fit values and bounds of the parameters are obtained at 66\%, 90\% and 99\% confidence levels which are shown by closed confidence contours in the figures. For the logarithmic model unbounded confidence contours are obtained and hence the model parameters could not be finitely constrained. The distance modulus $\mu$(z) against redshift $z$ has also been plotted for our predicted theoretical models for the best fit values of the parameters and compared with the observed Union2 data sample and SNe Type Ia 292 data and we have shown that our predicted theoretical models permits the observational data sets. From the data fitting it is seen that at lower redshifts $(z<0.3)$ the SNe Type Ia 292 data gives a better fit with our theoretical models compared to the Union2 data sample. So, from the data analysis, SNe Type Ia 292 data is the more favoured data sample over its counterpart given the present choice of free parameters. From the study, it is also seen that the logarithmic parametrization model is less supported by the observational data. Finally we have generated the plot for the deceleration parameter against the redshift parameter for all the theoretical models and compared the results with the work of Farooq et al, 2013.