Linear growth in power law<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

Basilakos, Spyros

doi:10.1103/physrevd.93.083007

Cited by 49 publications

(46 citation statements)

References 67 publications

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“…The general recipe is to consider by hand a variety of specific forms inside some general class, apply them in a cosmological framework, predict the dynamical behaviours at both the background and perturbation levels, and then use observational data to constrain the involved parameters or exclude the examined form (a similar procedure can also be followed to confront with local/solar system data). For the case of torsional gravity, the cosmological confrontations have been performed in [47][48][49][50][51][52][53][54], and the solar system tests can be found in [55][56][57], while the latest limit from galaxy lensing has been presented in [58]. Hence, in the literature there exist at least three viable scenarios for f (T ) gravity [48,53].…”

Section: Introductionmentioning

confidence: 99%

Model-independent Reconstruction of f(T) Gravity from Gaussian Processes

Cai

Khurshudyan

Saridakis

2020

ApJ

138

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We apply Gaussian processes and Hubble function data in f (T ) cosmology, to reconstruct for the first time the f (T ) form in a model-independent way. In particular, using H(z) datasets coming from cosmic chronometers as well as from the radial BAO method, alongside the latest released local value H0 = 73.52 ± 1.62 km/s/Mpc, we reconstruct H(z) and its derivatives, resulting eventually in a reconstructed region for f (T ), without any assumption. Although the cosmological constant lies in the central part of the reconstructed region, the obtained mean curve follows a quadratic function. Inspired by this we propose a new f (T ) parametrization, i.e. f (T ) = −2Λ + ξT 2 , with ξ the sole free parameter that quantifies the deviation from ΛCDM cosmology. Additionally, we confront three viable one-parameter f (T ) models of the literature, which respectively are the power-law, the square-root exponential, and the exponential one, with the reconstructed f (T ) region, and then we extract significantly improved constraints for their model parameters, comparing to the constraints that arise from usual observational analysis. Finally, we argue that since we are using the direct Hubble measurements and the local value for H0 in our analysis, with the above reconstruction of f (T ), the H0 tension can be efficiently alleviated.

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Section: Introductionmentioning

confidence: 99%

Model-independent Reconstruction of f(T) Gravity from Gaussian Processes

Cai

Khurshudyan

Saridakis

2020

ApJ

138

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“…Although some general features can be extracted through theoretical arguments, such as the existence of Noether symmetries, the absence of ghosts, the stability of perturbations, etc, the basic tool that one has is the confrontation with observations. In these lines, in the case of f (T ) gravity there has been a large amount of research towards this direction using solar system data [44][45][46], gravitational waves data [47][48][49], as well as cosmological ones [50][51][52][53][54][55][56][57][58][59][60].…”

Section: Introductionmentioning

confidence: 99%

Bayesian analysis off(T)gravity usingfσ8data

2019

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We use observational data from Supernovae (SNIa) Pantheon sample, from direct Hubble constant measurements with cosmic chronometers (CC), from the Cosmic Microwave Background shift parameter CMB shift , and from redshift space distortion (f σ8) measurements, in order to constrain f (T ) gravity. We do not follow the common γ parameterization within the semi-analytical approximation of the growth rate, in order to avoid model-dependent uncertainties. Up to our knowledge this is the first time that f (T ) gravity is 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 describe adequately the f σ8 data. Furthermore, 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 ΛCDM paradigm.

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“…In particular, we can set up a more general formalism in which the background expansion data, including SN Ia, BAO, CMB shift parameter, Hubble expansion data, joined with the growth rate data of LSSs in order to put constraints on the parameters of cosmology and DE models (see Cooray et al 2004;Corasaniti et al 2005;Mota et al 2007Mota et al , 2008Basilakos et al 2010;Gannouji et al 2010;Mota et al 2010;Blake et al 2011b;Nesseris et al 2011;Basilakos & Pouri 2012;Chuang et al 2013;Contreras et al 2013;Llinares & Mota 2013;Llinares et al 2014;Li et al 2014;Yang et al 2014;Basilakos 2015;Mehrabi et al 2015aMehrabi et al , 2015bBasilakos 2016;Bonilla Rivera & Farieta 2016;Fay 2016;Malekjani et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Constraints to Dark Energy Using PADE Parameterizations

Rezaei

Malekjani

Basilakos

et al. 2017

ApJ

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We put constraints on dark energy (DE) properties using PADE parameterization, and compare it to the same constraints using Chevalier-Polarski-Linder (CPL) and ΛCDM, at both the background and the perturbation levels. The DE equation of the state parameter of the models is derived following the mathematical treatment of PADE expansion. Unlike CPL parameterization, PADE approximation provides different forms of the equation of state parameter that avoid the divergence in the far future. Initially we perform a likelihood analysis in order to put constraints on the model parameters using solely background expansion data, and we find that all parameterizations are consistent with each other. Then, combining the expansion and the growth rate data, we test the viability of PADE parameterizations and compare them with CPL and ΛCDM models, respectively. Specifically, we find that the growth rate of the current PADE parameterizations is lower than ΛCDM model at low redshifts, while the differences among the models are negligible at high redshifts. In this context, we provide for the first time a growth index of linear matter perturbations in PADE cosmologies. Considering that DE is homogeneous, we recover the well-known asymptotic value of the growth index (namely . Finally, we generalize the growth index analysis in the case where γ is allowed to vary with redshift, and we find that the form of z g ( ) in PADE parameterization extends that of the CPL and ΛCDM cosmologies, respectively.

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Linear growth in power lawf(T)gravity

Cited by 49 publications

References 67 publications

Model-independent Reconstruction of f(T) Gravity from Gaussian Processes

Model-independent Reconstruction of f(T) Gravity from Gaussian Processes

Bayesian analysis off(T)gravity usingfσ8data

Constraints to Dark Energy Using PADE Parameterizations

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