This folder contains the H-EFTCAMB code.

Before installation, make sure you have the following dependencies installed:

• gfortran
• gcc
• lapack

By default, the blas and lapack library is linked by -lblas -llapack. If a custom library is used, change the variables BLASFLAG and LAPACK_FLAG in fortran/Makefile to point to your local blas and lapack library. The python wrapper further requires the following python packages:

• python3
• numpy
• sympy
• scipy
• packaging

For example, using conda, you can create a new environment and install the required packages with the following command:

conda create -n HEFTCAMB_env gfortran gcc lapack numpy python sympy scipy packaging -c conda-forge

Clone the H-EFTCAMB code using

git clone https://github.com/EFTCAMB/EFTCAMB.git --recursive

and navigate to the package directory and compile the code by typing:

cd fortran
make all

This will compile both the camb executive and the python wrapper. The executive and python wrapper are independent of each other. If you intend to call H-EFTCAMB only through python (recommended), you can compile the python wrapper only by make python. The compiled python library locates in the folder camb in the root directory and can be imported in the same way as the original CAMB by

import camb

Note for Mac Users: If you're using a Mac with an Apple Silicon chip (e.g., M1, M2), make sure you install the appropriate version of fortran and C compilers for your architecture (arm64), for example:

conda create -n HEFTCAMB_env gfortran_osx-arm64 clang_osx-arm64 lapack numpy python sympy scipy packaging -c conda-forge

and set the environment variable CC to point to the correct C compiler before installation. You can check the versions by typing gfortran -v and clang -v. Make sure that your python3 is compiled with the same C compiler.

The contents of H-EFTCAMB are listed in this chart:

We provide a set of notes that contain all the details and formulas of the EFTCAMB implementation:

• EFTCAMB/EFTCosmoMC: Numerical Notes v3.0 Bin Hu, Marco Raveri, Noemi Frusciante, Alessandra Silvestri, arXiv:1405.3590 [astro-ph.CO]

with the new additions to H-EFTCAMB described in:

• H-EFTCAMB: A Cobaya-Integrated, Python-Wrapped Extension of EFTCAMB for Covariant Horndeski Gravity Gen Ye, Shijie Lin, Jiaming Pan, Dani de Boe, Stan Verhoeve, Marco Raveri, Bin Hu, Noemi Frusciante, Alessandra Silvestri, arXiv:2603.01662 [gr-qc]

The H-EFTCAMB source files documentation is automatically built at any modification of the code and can be found at this link.

Besides above documentation, there are several flowchart or markdown files helping you easily find your model flags and set parameters in “find_your_model" folder.

The H-EFTCAMB distribution contains a folder called example containing some example notebooks demonstrating how to setup and run various dark energy / modified gravity models and extract results for analysis using the python wrapper. The folder also contains several example Cobaya input files demonstrating how to analyze dark energy / modified gravity models with H-EFTCAMB in Cobaya.

For further instructions on the usage of Cobaya, refer to the its documentation at: https://readthedocs.org/projects/cobaya/badge/?version=latest

If you use the EFTCAMB/EFTCosmoMC package, please refer the original CAMB paper and ours:

• Effective Field Theory of Cosmic Acceleration: an implementation in CAMB Bin Hu, Marco Raveri, Noemi Frusciante, Alessandra Silvestri, arXiv:1312.5742 [astro-ph.CO] Phys.Rev. D89 (2014) 103530

• Effective Field Theory of Cosmic Acceleration: constraining dark energy with CMB data Marco Raveri, Bin Hu, Noemi Frusciante, Alessandra Silvestri, arXiv:1405.1022 [astro-ph.CO] Phys.Rev. D90 (2014) 043513

• H-EFTCAMB: A Cobaya-Integrated, Python-Wrapped Extension of EFTCAMB for Covariant Horndeski Gravity Gen Ye, Shijie Lin, Jiaming Pan, Dani de Boe, Stan Verhoeve, Marco Raveri, Bin Hu, Noemi Frusciante, Alessandra Silvestri, arXiv:2603.01662 [gr-qc]

This is the usual, fair way of giving credit to contributors to a scientific result. In addition, it helps us justify our effort in developing the H-EFTCAMB code as an academic undertaking.

H-EFTCAMB is a modification of the CAMB code. The code part of CAMB that is not modified is copyrighted by the CAMB authors and released under their licence.

For the part of code that constitutes H-EFTCAMB see the LICENSE file in eftcamb/LICENSE.

In addition to CAMB makefile targets H-EFTCAMB comes with the additional:

• eftcamb: to compile H-EFTCAMB;
• eftcamb_apps: to compile H-EFTCAMB applications like the benchmarker;
• eftcamb_dep: to automatically sort out H-EFTCAMB source file dependencies;
• eftcamb_doc: to build the H-EFTCAMB automatic documentation;
• intel_profile: to compile H-EFTCAMB with the options that allow profiling with the VTUNE profiler;
• profile: to compile H-EFTCAMB with the options that allow general profiling;

In the folder eftcamb all the source files for H-EFTCAMB are stored. In an effort to have small and readable files the the naming convention allows to have an intuition of the hierarchy of the code from alphabetical order of files.

For this reason we use the following convention for the prefixes:

• 01_ compile time utilities;
• 02_ pure and general purpose algorithms;
• 03_ EFTCAMB cache containing the storage for all cosmological quantities of interest;
• 04_ general parametrizations for 1D functions;
• 05_ general parametrizations for 2D functions;
• 06_ abstract implementation of EFT models;
• 07_ implementation of models that requires input background;
• 08_ implementation of models that solves for the background;
• 09_ general EFT algorithms (RGR, stability, init);
• 10_ EFT background output support;
• 11_ implementation of functions exposed to the python wrapper;

If you modify or add one or more files make sure to issue make eftcamb_dep before compiling the code to ensure that all dependencies are properly sorted out and built.