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Bayesian analysis of f(T) gravity using fσ8 data

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We use observational data from the Pantheon supernovae sample, direct Hubble constant measurements with cosmic chronometers, the cosmic microwave background shift parameter CMBshift, and redshift-space distortion (fσ8) measurements, in order… Click to show full abstract

We use observational data from the Pantheon supernovae sample, direct Hubble constant measurements with cosmic chronometers, the cosmic microwave background shift parameter CMBshift, and redshift-space distortion (fσ8) measurements, in order to constrain f(T) gravity. We do not follow the common γ parametrization within the semianalytical approximation of the growth rate, in order to avoid model-dependent uncertainties. To our knowledge this is the first time that f(T) gravity has been analyzed within a Bayesian framework, and with background and perturbation behaviour considered jointly. We show that all three examined f(T) models are able to adequately describe the fσ8 data. Furthermore, by applying the Akaike, Bayesian and deviance information criteria, we conclude that all considered models are statistically equivalent; however the most efficient candidate is the exponential model, which additionally presents a small deviation from the ΛCDM paradigm.

Keywords: bayesian analysis; analysis gravity; using data; gravity; gravity using

Journal Title: Physical Review D
Year Published: 2019

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