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Cosmological dynamics of dark energy in scalar-torsion $f(T,\phi)$ gravity

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arxiv 2011.08377 v4 pith:6B3HX7TT submitted 2020-11-17 gr-qc astro-ph.COhep-th

classification gr-qcastro-ph.COhep-th
keywords darkenergygravityscalingcosmologicalsolutionsdensitydynamics
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abstract

It is investigated the cosmological dynamics of scalar-torsion $f(T,\phi)$ gravity as a dark energy model, where $T$ is the torsion scalar of teleparallel gravity and $\phi$ is a canonical scalar field. In this context, we are concerned with the phenomenology of the class of models with non-linear coupling to gravity and exponential potential. We obtain the critical points of the autonomous system, along with the stability conditions of each one of them and their cosmological properties. Particularly, we show the existence of new attractors with accelerated expansion, as well as, new scaling solutions in which the energy density of dark energy scales as the background fluid density, thus, defining the so-called scaling radiation and scaling matter epochs. The scaling solutions are saddle points, and therefore, the system exits these solutions to the current epoch of cosmic acceleration, towards an attractor point describing the dark energy-dominated era.

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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. Higgs-like inflation in scalar-torsion $f(T,\phi)$ gravity in light of ACT-SPT-DESI constraints

    gr-qc 2025-12 conditional novelty 5.0 of 10

    Higgs-like inflation in f(T,φ) torsion gravity can accommodate the ACT/DESI upward shift in the scalar spectral index while predicting a tensor-to-scalar ratio r≈0.01–0.04.

  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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