explores the application of observational data to constrain gravi- tational models

Abstract

This thesis explores the application of observational data to constrain gravi- tational models within the framework of f(G, T ) gravity, focusing on cosmol- ogy. Three distinct models were investigated: f(G, T ) = βGn + γT , f(G, T ) = βG + ηemT , and f(G, T ) = βGn + λ √ −T . Using Python-based analysis, the Hubble parameter H(z) functions were derived from these models by applying the gravity equations and the equation of state (EoS). Key cosmographic pa- rameters, including the deceleration parameter q(z), jerk parameter j(z), snap parameter s(z), and lerk parameter l(z), were calculated and analyzed. By gen- erating plots of H(z) and the cosmographic parameters for various values of the constants (β, γ, η, λ), the sensitivity of the models to these parameters was assessed. The results highlight the significance of accurately selecting these con- stants to describe the universe expansion dynamics, demonstrating the impor- tance of observational data in constraining gravitational models.