$\mathcal{H}$-EFTCAMB: A Cobaya-Integrated, Python-Wrapped Extension of EFTCAMB for Covariant Horndeski Gravity
Abstract
We present , the official successor to . The original is designed as a consistent and numerically stable implementation of the effective field theory (EFT) of dark energy in the Einstein-Boltzmann code . On top of this, introduces a new Horndeski module that supports computing cosmology for an arbitrary input covariant Horndeski Lagragian. 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 and externally with . features a flexible Python wrapper that is seamlessly integrated into the widely utilized cosmological sampler . \heft~is publicly available and serves as a comprehensive tool for testing gravity against the precision data from current and next-generation surveys.
Cite
@article{arxiv.2603.01662,
title = {$\mathcal{H}$-EFTCAMB: A Cobaya-Integrated, Python-Wrapped Extension of EFTCAMB for Covariant Horndeski Gravity},
author = {Gen Ye and Shijie Lin and Jiaming Pan and Dani de Boe and Stan Verhoeve and Marco Raveri and Bin Hu and Noemi Frusciante and Alessandra Silvestri},
journal= {arXiv preprint arXiv:2603.01662},
year = {2026}
}
Comments
15 pages, 7 figures, code available at https://github.com/EFTCAMB/EFTCAMB; v2 correct typos and add references