Lyman-alpha Cosmology Emulator. This code is a normalising flow emulator for the 3D flux power spectrum of the Lyman-alpha forest.
These are the parameters that describe each individual P3D(k, mu) 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
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
In the Notebooks
folder, there are several tutorials one can run to learn how to use
the emulators and archives.
- Archive tutorial: notebooks/Tutorial_archive.ipynb
- Emulator tutorial: notebooks/Tutorial_emulator.ipynb
(Last update 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 forestflow -c conda-forge python=3.11 camb fdasrsf pip=24.0
conda activate forestflow
- Install LaCE:
Follow the instructions from https://github.com/igmhub/LaCE
- Clone the ForestFlow repo and perform an editable installation:
git clone https://github.com/igmhub/ForestFlow.git
cd ForestFlow
pip install -e . [jupyter] # try with or without space between the . and jupyter if you need it
- Generate notebooks:
pip install jupytext
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 forestflow --display-name forestflow
- If you want to use Px routines, you need to install hankl:
pip install -e .[px]