JAX-based emulator for galaxy power spectra with bias modeling and EFT corrections.
- Stable Documentation - Latest release documentation
- Development Documentation - Latest development version documentation
In order to install jaxeffort, you can just run
pip install jaxeffortIf you prefer to use the latest version from the repository, you can clone it, enter it, and run
pip install .In order to use the emulators, you have to import jaxeffort and load a trained emulator
import jaxeffort
import jax.numpy as np
trained_emu = jaxeffort.load_multipole_emulator("/path/to/emu/")Then you are good to go! You have to create input arrays for cosmological and bias parameters and retrieve your calculation result
cosmo_params = np.array([...]) # cosmological parameters
bias_params = np.array([...]) # bias parameters
result = trained_emu.get_Pl(cosmo_params, bias_params, D)For a more detailed explanation, check the tutorial in the notebooks folder, which also shows a comparison with standard power spectrum calculations.
Free usage of the software in this repository is provided, given that you cite our release paper.
M. Bonici, G. D'Amico, J. Bel, C. Carbone, Effort.jl: a fast and differentiable emulator for the Effective Field Theory of the Large Scale Structure of the Universe, JCAP 09 (2025) 044
@article{Bonici_2025,
doi = {10.1088/1475-7516/2025/09/044},
url = {https://dx.doi.org/10.1088/1475-7516/2025/09/044},
year = {2025},
month = {sep},
publisher = {IOP Publishing},
volume = {2025},
number = {09},
pages = {044},
author = {Bonici, Marco and D'Amico, Guido and Bel, Julien and Carbone, Carmelita},
title = {Effort.jl: a fast and differentiable emulator for the Effective Field Theory of the Large Scale Structure of the Universe},
journal = {Journal of Cosmology and Astroparticle Physics}
}