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Can $f(Q)$ gravity challenge $\Lambda$CDM?

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arxiv 2108.10832 v2 pith:WAAIOR5Z submitted 2021-08-24 astro-ph.CO gr-qc

Luís Atayde , Noemi Frusciante This is my paper · ORCID
classification astro-ph.COgr-qc
keywords lambdabackgroundconstraintsgravitationalgravitylinearmodelsnia
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abstract

We study observational constraints on the non-metricity $f(Q)$-gravity which reproduces an exact $\Lambda$CDM background expansion history while modifying the evolution of linear perturbations. To this purpose we use Cosmic Microwave Background (CMB) radiation, baryonic acoustic oscillations (BAO), redshift-space distortions (RSD), supernovae type Ia (SNIa), galaxy clustering (GC) and weak gravitational lensing (WL) measurements. We set stringent constraints on the parameter of the model controlling the modifications to the gravitational interaction at linear perturbation level. We find the model to be statistically preferred by data over the $\Lambda$CDM according to the $\chi^2$ and deviance information criterion statistics for the combination with CMB, BAO, RSD and SNIa. This is mostly associated to a better fit to the low-$\ell$ tail of CMB temperature anisotropies.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Decoupling perturbations from background in $f(Q)$ gravity: the square-root correction and the impact on the $\sigma_8$ tension

    astro-ph.CO 2025-12 conditional novelty 4.0 of 10

    A sqrt(Q) correction in f(Q) gravity suppresses structure growth without altering the expansion history; fitted to RSD/DESI data it can bring sigma8 into agreement with Planck, at the cost of a sigma8-M degeneracy.

  2. Dynamical Dark Energy or Modified Gravity? Signatures in Gravitational Wave Propagation

    gr-qc 2025-09 conditional novelty 4.0 of 10

    Reconstructing the dark energy density from DESI BAO and DESyr5 supernovae, then recasting it as f(Q) gravity, predicts a low-redshift gravitational wave damping ν≈0.18 (≳2σ from GR) only for the DESyr5 dataset.

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