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Bayesian analysis of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>f</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mi>T</mml:mi><mml:mo stretchy="false">)</mml:mo></mml:math>gravity using<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi>f</mml:mi><mml:msub><mml:mrow><mml:mi>σ</mml:mi></mml:mrow><mml:mrow><mml:mn>8</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math>data

Fotios K. AnagnostopoulosDepartment of Physics, National & Kapodistrian University of Athens, Zografou Campus GR 157 73 Athens, GreeceSpyros BasilakosAcademy of Athens, Research Center for Astronomy and Applied Mathematics, Soranou Efesiou 4, 11527 Athens, GreeceEmmanuel N. SaridakisChongqing University of Posts & Telecommunications, Chongqing 400065, P.R. China
2019lv
ABI

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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 ${\mathrm{CMB}}_{\text{shift}}$, and redshift-space distortion ($f{\ensuremath{\sigma}}_{8}$) measurements, in order to constrain $f(T)$ gravity. We do not follow the common $\ensuremath{\gamma}$ 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 $f{\ensuremath{\sigma}}_{8}$ 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 $\mathrm{\ensuremath{\Lambda}}\mathrm{CDM}$ paradigm.

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