A Bayesian Statistical Study of Bianchi Type-I Universe in $f(R,T^\psi)$ Modified Gravity
Mohit Thakre, Praveen Kumar Dhankar, Safiqul Islam, Parbati Sahoo, Farook Rahaman, Behnam Pourhassan

TL;DR
This paper investigates an anisotropic Bianchi Type-I universe model within $f(R,T^ psi)$ gravity, using Bayesian methods and observational data to constrain parameters and demonstrate compatibility with late-time cosmic acceleration.
Contribution
It applies Bayesian statistical techniques and MCMC analysis to constrain an extended gravity model with observational data, exploring anisotropic cosmology.
Findings
Model aligns with observational data and describes late-time acceleration.
Statistical analysis confirms model's stability and consistency.
Comparison with $ Lambda$CDM supports the model's reliability.
Abstract
We have examined the cosmological actions of LRS (Locally Rationally Symmetric) Bianchi type-I universe model in gravity. For this, we have estimated the Hubble parameter, the effective equation of state parameter (), and the potential of the scalar field as a function of time using equation . The graphical representation of the potential function with respect to cosmic time t is described. This study explores the dynamical properties of a Bianchi Type-I universe by utilizing Bayesian statistical techniques to constrain the model parameters and evaluate the viability of anisotropic cosmology under extended matter-geometry couplings. Also, we have applied the Markov Chain Monte Carlo (MCMC) mechanism on the derived model by using observational Hubble data (OHD), the Baryon Acoustic Oscillation (BAO) dataset, and the Pantheon…
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Taxonomy
TopicsCosmology and Gravitation Theories · Galaxies: Formation, Evolution, Phenomena · Statistical Mechanics and Entropy
