4.5 Article

Anisotropic Universe in f (Q, T) gravity, a novel study

期刊

ANNALS OF PHYSICS
卷 454, 期 -, 页码 -

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ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.aop.2023.169333

关键词

f(Q; T) gravity; Symmetric teleparallel theory; Dark Energy; Accelerating expansion; Cosmology

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The f(Q, T) theory of gravity, which incorporates the trace T of the energy-momentum tensor and the non-metricity scalar Q, has been well-studied in the cosmological application. However, considering the anisotropy of our Universe since the Planck era, it is necessary to investigate this theory in a model with small anisotropy for a complete understanding of the Universe's evolution. By using a locally rotationally symmetric (LRS) Bianchi-I spacetime and deriving the motion equations, we analyzed the model candidate f(Q, T) = & alpha;Qn+1 + & beta;T and constrained the parameter n using statistical Markov chain Monte Carlo (MCMC) method with the Bayesian approach and two independent observational datasets, namely the Hubble datasets and Type Ia supernovae (SNe Ia) datasets.
f(Q, T) theory of gravity is very recently proposed to incorpo-rate within the action Lagrangian, the trace T of the energy- momentum tensor along with the non-metricity scalar Q. The cosmological application of this theory in a spatially flat isotropic and homogeneous Universe is well-studied. However, our Uni-verse is not isotropic since the Planck era and therefore to study a complete evolution of the Universe we must investigate the f (Q, T) theory in a model with a small anisotropy. This motivated us to presume a locally rotationally symmetric (LRS) Bianchi -I spacetime and derive the motion equations. We analyse the model candidate f(Q, T) = & alpha;Qn+1 + & beta;T, and to constrain the parameter n, we employ the statistical Markov chain Monte Carlo (MCMC) method with the Bayesian approach using two independent observational datasets, namely, the Hubble datasets, and Type Ia supernovae (SNe Ia) datasets.& COPY; 2023 Elsevier Inc. All rights reserved.

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