Paper
$\mathcal{H}$-EFTCAMB: A Cobaya-Integrated, Python-Wrapped Extension of EFTCAMB for Covariant Horndeski Gravity
Authors
Gen Ye, Shijie Lin, Jiaming Pan, Dani de Boe, Stan Verhoeve, Marco Raveri, Bin Hu, Noemi Frusciante, Alessandra Silvestri
Abstract
We present $\mathcal{H}\mathtt{-EFTCAMB}$, the official successor to $\mathtt{EFTCAMB}$. The original $\mathtt{EFTCAMB}$ is designed as a consistent and numerically stable implementation of the effective field theory (EFT) of dark energy in the Einstein-Boltzmann code $\mathtt{CAMB}$. On top of this, $\mathcal{H}\mathtt{-EFTCAMB}$ introduces a new Horndeski module that supports computing cosmology for an arbitrary input covariant Horndeski Lagragian. $\mathcal{H}\mathtt{-EFTCAMB}$ supports both mapping the Horndeski theory to an EFT lagrangian to solve in the EFT framework as well as directly solving for the scalar field equations of motion derived from the covariant Lagrangian. The latter approach also works for the cases when the Horndeski field experiences turn-overs, e.g. oscillation, where the EFT approach breaks down. The Horndeski module has been validated by comparing internally with existing models in the original $\mathtt{EFTCAMB}$ and externally with $\mathtt{hi\_class}$. $\mathcal{H}\mathtt{-EFTCAMB}$ features a flexible Python wrapper that is seamlessly integrated into the widely utilized cosmological sampler $\mathtt{Cobaya}$. \heft~is publicly available and serves as a comprehensive tool for testing gravity against the precision data from current and next-generation surveys.
Metadata
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Raw Data (Debug)
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"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2603.01662v1</id>\n <title>$\\mathcal{H}$-EFTCAMB: A Cobaya-Integrated, Python-Wrapped Extension of EFTCAMB for Covariant Horndeski Gravity</title>\n <updated>2026-03-02T09:52:29Z</updated>\n <link href='https://arxiv.org/abs/2603.01662v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2603.01662v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>We present $\\mathcal{H}\\mathtt{-EFTCAMB}$, the official successor to $\\mathtt{EFTCAMB}$. The original $\\mathtt{EFTCAMB}$ is designed as a consistent and numerically stable implementation of the effective field theory (EFT) of dark energy in the Einstein-Boltzmann code $\\mathtt{CAMB}$. On top of this, $\\mathcal{H}\\mathtt{-EFTCAMB}$ introduces a new Horndeski module that supports computing cosmology for an arbitrary input covariant Horndeski Lagragian. $\\mathcal{H}\\mathtt{-EFTCAMB}$ supports both mapping the Horndeski theory to an EFT lagrangian to solve in the EFT framework as well as directly solving for the scalar field equations of motion derived from the covariant Lagrangian. The latter approach also works for the cases when the Horndeski field experiences turn-overs, e.g. oscillation, where the EFT approach breaks down. The Horndeski module has been validated by comparing internally with existing models in the original $\\mathtt{EFTCAMB}$ and externally with $\\mathtt{hi\\_class}$. $\\mathcal{H}\\mathtt{-EFTCAMB}$ features a flexible Python wrapper that is seamlessly integrated into the widely utilized cosmological sampler $\\mathtt{Cobaya}$. \\heft~is publicly available and serves as a comprehensive tool for testing gravity against the precision data from current and next-generation surveys.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='gr-qc'/>\n <category scheme='http://arxiv.org/schemas/atom' term='astro-ph.IM'/>\n <published>2026-03-02T09:52:29Z</published>\n <arxiv:comment>15 pages, 7 figures, code available at https://github.com/EFTCAMB/EFTCAMB</arxiv:comment>\n <arxiv:primary_category term='gr-qc'/>\n <author>\n <name>Gen Ye</name>\n </author>\n <author>\n <name>Shijie Lin</name>\n </author>\n <author>\n <name>Jiaming Pan</name>\n </author>\n <author>\n <name>Dani de Boe</name>\n </author>\n <author>\n <name>Stan Verhoeve</name>\n </author>\n <author>\n <name>Marco Raveri</name>\n </author>\n <author>\n <name>Bin Hu</name>\n </author>\n <author>\n <name>Noemi Frusciante</name>\n </author>\n <author>\n <name>Alessandra Silvestri</name>\n </author>\n </entry>"
}