igmhub / LaCE

Emulator for the one-dimensional Lyman-alpha flux power spectrum. It was used to generate the results shown in https://arxiv.org/abs/2011.15127, https://arxiv.org/abs/2209.09895, and https://arxiv.org/abs/2305.19064.
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LaCE

LaCE contains a set of emulators for the one-dimensional flux power spectrum of the Lyman-alpha forest. It has been used in the papers:

Please cite at least https://arxiv.org/abs/2305.19064 if you use this emulator in your research.

Installation

(Last updated: Jan 19 2024)

conda create -n lace -c conda-forge python=3.11 camb fdasrsf
conda activate lace
pip install --upgrade pip
git clone https://github.com/igmhub/LaCE.git
cd LacE
pip install -e .
pip install -e .[explicit]

Tests

Please run the following script to check that the package is working properly.

python test_lace.py

Nyx users:

 "env": {
  "NYX_PATH":"path_to_Nyx"
 }

You also need to add the Nyx path as an environment variable. The Nyx data is located at NERSC in

NYX_PATH="/global/cfs/cdirs/desi/science/lya/y1-p1d/likelihood_files/nyx_files/"
python scripts/save_nyx_emu_cosmo.py
python scripts/save_nyx_IGM.py

Emulator parameters:

These are the parameters that describe each individual P1D(k) power spectrum. We have detached these from redshift and traditional cosmology parameters.

Cosmological parameters:

Delta2_p is the amplitude of the (dimensionless) linear spectrum at k_p = 0.7 1/Mpc

n_p is the slope of the linear power spectrum at k_p

alpha_p is the running of the linear power spectrum at k_p

f_p is the (scale-independent) logarithmic growth rate

The current version of the emulator, relased in this repo, does not emulate alpha_p and f_p. However, these parameters are stored in the P1D archive.

IGM parameters:

mF is the mean transmitted flux fraction in the box (mean flux)

sigT_Mpc is the thermal broadening scale in comoving units, computed from T_0 in the temperature-density relation

gamma is the slope of the temperature-density relation

kF_Mpc is the filtering length (or pressure smoothing scale) in inverse comoving units

Notebooks / tutorials

jupytext --to ipynb notebooks/*.py
pip install ipykernel
python -m ipykernel install --user --name cup1d --display-name lace

In the Notebooks folder, there are several tutorials one can run to learn how to use the archives and emulators.