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Cited by 289

The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.

Vector field models of inflation and dark energy

Open access
Koivisto, Tomi, Mota, David F·2008·Journal of Cosmology and Astroparticle Physics

Abstract

We consider several new classes of viable vector field alternatives to the inflaton and quintessence scalar fields. Spatial vector fields are shown to be compatible with the cosmological anisotropy bounds if only slightly displaced from the potential minimum while dominant, or if driving an anisotropic expansion with nearly vanishing quadrupole today. The Bianchi I model with a spatial field and an isotropic fluid is studied as a dynamical system, and scaling solutions of several types are found. On the other hand, time-like fields are automatically compatible with large-scale isotropy. We show that they can be dynamically important if non-minimal gravity couplings are taken into account. We reconstruct as an example a vector–Gauss–Bonnet model which generates the concordance model acceleration at late times and supports an inflationary epoch at high curvatures. The evolution of the vortical perturbations in such models is computed.

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Crossref · 10.1088/1475-7516/2008/08/021

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Metadata

Authors
Koivisto, T., & Mota, D. F.
Venue
Journal of Cosmology and Astroparticle Physics
Published
2008-08-15
Volume
2008
Issue
08
Pages
021
ISSN
  • 1475-7508 (ISSN-L)
  • 1475-7516
OpenAlex
W2000914920
Cited by
289
References
78
FWCI
14.93
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Vector field models of inflation and dark energy. https://app.cochat.ai/papers/10.1088/1475-7516/2008/08/021
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Koivisto, T., & Mota, D. F. (2008). Vector field models of inflation and dark energy. Journal of Cosmology and Astroparticle Physics. https://doi.org/10.1088/1475-7516/2008/08/021

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.