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Observational constraints and cosmological implications of scalar–tensor f(R,T) gravity

A. Bouali, H. Chaudhary, T. Harko, F. S. N. Lobo, T. Ouali, M. Pinto

Recently, the scalar–tensor representation of f(R,T) gravity was used to explore gravitationally induced particle production/annihilation. Using the framework of irreversible thermodynamics of open systems in the presence of matter creation/annihilation, the physical and cosmological consequences of this setup were investigated in detail. In this paper, we test observationally the scalar–tensor representation of f(R,T) gravity in the context of the aforementioned framework, using the Hubble and Pantheon + measurements. The best fit parameters are obtained by solving numerically the modified Friedmann equations of two distinct cosmological models in scalar–tensor f(R,T) gravity, corresponding to two different choices of the potential, and by performing a Markov Chain Monte Carlo analysis. The best parameters are used to compute the cosmographic parameters, that is, the deceleration, the jerk, and the snap parameters. Using the output resulting from the Markov Chain Monte Carlo analysis, the cosmological evolution of the creation pressure and of the matter creation rates are presented for both models. To figure out the statistical significance of the studied scalar–tensor f(R,T) gravity, the Bayesian and the corrected Akaike information criteria are used. The latter indicates that the first considered model in scalar–tensor f(R,T) gravity is statistically better than ΛCDM, that is, it is more favoured by observations. Besides, a continuous particle creation process is present in Model 1. Alternatively, for large redshifts, in Model 2 the particle creation rate may become negative, thus indicating the presence of particle annihilation processes. However, both models lead to an accelerating expansion of the universe at late times, with a deceleration parameter equivalent to that of the ΛCDM model.

cosmology: observations, dark energy, methods: statistical, methods: numerical, methods: data analysis, miscellaneous

Monthly Notices of the Royal Astronomical Society
Volume 526, Issue 3, Page 16
2023 December

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Faculdade de Ciências da Universidade de Lisboa Universidade do Porto Faculdade de Ciências e Tecnologia da Universidade de Coimbra
Fundação para a Ciência e a Tecnologia COMPETE 2020 PORTUGAL 2020 União Europeia