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:
- https://arxiv.org/abs/2011.15127
- https://arxiv.org/abs/2209.09895
- https://arxiv.org/abs/2305.19064 (latest version)
Please cite at least https://arxiv.org/abs/2305.19064 if you use this emulator in your research.
(Last updated: Jan 19 2024)
- Create a new conda environment. It is usually better to follow python version one or two behind. In January 2024, the latest is 3.12, so we recommend 3.11.
conda create -n lace -c conda-forge python=3.11 camb fdasrsf
conda activate lace
pip install --upgrade pip
- Clone the repo into your machine and perform an editable installation:
git clone https://github.com/igmhub/LaCE.git
cd LacE
pip install -e .
- If you find problems, please install LaCE as follows:
pip install -e .[explicit]
Please run the following script to check that the package is working properly.
python test_lace.py
- You may need to add the Nyx path as an environment variable in your notebook kernel. The first is done by writing in the kernel.json file:
"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/"
- Before running LaCE, please precompute all cosmological information needed using CAMB and save IGM histories. This is done by running the following scripts. You do not need to do it if you are in NERSC.
python scripts/save_nyx_emu_cosmo.py
python scripts/save_nyx_IGM.py
These are the parameters that describe each individual P1D(k) power spectrum. We have detached these from redshift and traditional cosmology 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.
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
- All notebooks in the repository are in .py format. To generate the .ipynb version, run:
jupytext --to ipynb notebooks/*.py
- If you want to use notebooks via JupyterHub, you'll also need to download
ipykernel
:
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.
- Archive tutorial: notebooks/Tutorial_bookkeeping.py
- Emulator tutorial: notebooks/Tutorial_emulator.py