Observational Study of Higher Dimensional Magnetic Universe in Non-linear Electrodynamics

TL;DR

This study explores higher-dimensional magnetic universe models within non-linear electrodynamics, analyzing their expansion behavior and fitting parameters using observational data across different dimensions.

Contribution

It provides a comparative analysis of higher-dimensional magnetic universe models, fitting observational data and constraining parameters for 4D, 5D, and 6D cases.

Findings

Best-fit parameters obtained at 66%, 90%, 99% confidence levels.

Higher dimensions influence the magnetic field and deceleration parameter.

Model fits well with Supernova Type Ia data across dimensions.

Abstract

In this work, we have considered the flat FRW model of the universe in $(n+2)$-dimensions filled with the dark matter and the magnetic field. We present the Hubble parameter in terms of the observable parameters $\Omega_{m0}$ and $H_{0}$ with the redshift $z$ and the other parameters like $B_{0},\omega, \mu_{0},\delta,n,w_{m}$. The natures of magnetic field $B$, deceleration parameter $q$ and $Om$ diagnostic have also been analyzed for accelerating expansion of the universe. From Stern data set (12 points), we have obtained the bounds of the arbitrary parameters by minimizing the $\chi^{2}$ test. The best-fit values of the parameters are obtained by 66%, 90% and 99% confidence levels. Now to find the bounds of the parameters ($B_{0},\omega$) and to draw the statistical confidence contour, we fixed four parameters $\mu_{0},\delta,n,w_{m}$. Here the parameter $n$ determines the higher dimensions and we perform comparative study between three cases : 4D $(n=2)$, 5D $(n=3)$ and 6D $(n=4)$ respectively. Next due to joint analysis with BAO observation, we have also obtained the bounds of the parameters ($B_{0},\omega$) by fixing other parameters $\mu_{0},\delta,n,w_{m}$ for 4D, 5D and 6D. The best fit of distance modulus for our theoretical model and the Supernova Type Ia Union2 sample are drawn for different dimensions.