cup1d

Cosmology using P1D - small-scale clustering of the Lyman alpha forest

This repository contains some tools to perform the last steps of a cosmological analysis of the 1D power spectrum (P1D) of the Lyman alpha forest.

It uses the LaCE emulator (https://github.com/igmhub/LaCE), and some extra tools to run MCMC analyses on cosmological and IGM parameters for a mock P1D measurement.

If you would like to collaborate, please email Andreu Font-Ribera (afont@ifae.es) or Jonas Chaves-Montero (jchaves@ifae.es).

Installation

• Download and install Conda. You can find the instructions here https://docs.anaconda.com/miniconda/miniconda-install/

• 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 cup1d -c conda-forge python=3.11 camb mpich mpi4py fdasrsf
conda activate cup1d
pip install --upgrade pip

• Clone and install LaCE (do so within the environment created above):

git clone https://github.com/igmhub/LaCE.git
cd LacE
pip install -e .

• Clone and install cup1d:

git clone https://github.com/igmhub/cup1d.git
cd cup1d
pip install -e .

NERSC users:

• You need to compile mpi4py package on NERSC (see here).

MPICC="cc -shared" pip install --force-reinstall --no-cache-dir --no-binary=mpi4py mpi4py

Nyx users:

• 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 cup1d, 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 LaCE/scripts/save_nyx_emu_cosmo.py
python LaCE/scripts/save_nyx_IGM.py

Notebooks / tutorials

• 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 cup1d

You can find the main tutorial to run your analyses in notebooks/tutorials/sample_sim.py

You can also plot many P1D measurements stored in the repo, by looking at notebooks/p1d_measurements

You can also redo old neutrino mass constraints by importance sampling WMAP and Planck chains, following notebooks/planck

You can also play with the LaCE emulator with the notebooks in notebooks/emulator

Forecasting script

You can use the script scripts/sam_sim.py to run your own analyses. It is fully parallelized using MPI.