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The growth of matter perturbations in f(R) models

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arxiv 0809.3374 v2 pith:6UDTIKRY submitted 2008-09-19 astro-ph gr-qc

classification astro-phgr-qc
keywords gammamodelssimeqgrowthomegaperturbationsredshiftsclear
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abstract

We consider the linear growth of matter perturbations on low redshifts in some $f(R)$ dark energy (DE) models. We discuss the definition of dark energy (DE) in these models and show the differences with scalar-tensor DE models. For the $f(R)$ model recently proposed by Starobinsky we show that the growth parameter $\gamma_0\equiv \gamma(z=0)$ takes the value $\gamma_0\simeq 0.4$ for $\Omega_{m,0}=0.32$ and $\gamma_0\simeq 0.43$ for $\Omega_{m,0}=0.23$, allowing for a clear distinction from $\Lambda$CDM. Though a scale-dependence appears in the growth of perturbations on higher redshifts, we find no dispersion for $\gamma(z)$ on low redshifts up to $z\sim 0.3$, $\gamma(z)$ is also quasi-linear in this interval. At redshift $z=0.5$, the dispersion is still small with $\Delta \gamma\simeq 0.01$. As for some scalar-tensor models, we find here too a large value for $\gamma'_0\equiv \frac{d\gamma}{dz}(z=0)$, $\gamma'_0\simeq -0.25$ for $\Omega_{m,0}=0.32$ and $\gamma'_0\simeq -0.18$ for $\Omega_{m,0}=0.23$. These values are largely outside the range found for DE models in General Relativity (GR). This clear signature provides a powerful constraint on these models.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 121 citations worldwide. Full citation record

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    astro-ph.CO 2026-07 accept novelty 4.0 of 10

    SKAO HI intensity mapping forecasts yield competitive LambdaCDM constraints (e.g. H0 to ~0.3 km/s/Mpc optimistic) via power spectrum, BAO, bispectrum and stacking, complementary to CMB and optical surveys.

  2. Late Time Phenomena in $f(T,\mathcal{T})$ Gravity Framework: Role of $H_0$ Priors

    gr-qc 2024-11 conditional novelty 4.0 of 10

    An f(T,T) gravity model fitted to Pantheon+, BAO, and cosmic chronometer data yields a range of H0 posteriors that track the input priors, and predicts a growth rate about 9-11% below ΛCDM for two data combinations.

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