Line Intensity map X Ly-Alpha forest (LILA)

Forecasting the cross-orrelation between Line Intensity map and Ly-Alpha Forest surveys

This repo containts a python package written for Qezlou et al. 2023 which forecasts the 3D auto and cross power-spectra for Ly-alpha forest, CO Line intensity map COMAP and galaxy redshift surveys.

The story behind the name:

Lila is a name for girls with Arabic, Persian, and Hindi roots, meaning "night" or "play". One famous reference to this name is the tale of "Layla" (another spelling) and "Majnun", an ancient Arab story about the poet Qays from the 7th century and his beloved Layla. The story was later passed on to Persian culture through a beautiful poem written by Nizami Ganjavi between 584-1188. "Layla and Majnun" is also called the Eastern version of Romeo and Juliet.

Installation

It requires python version < 3.9

You can install this simply by clonning this repo and then installing :

git clone https://github.com/qezlou/lila.git
cd lila
python -m pip install -e .

Note: We refrain from uploading the package to the Python Package Index (PyPI) because a package with the same name already exists, albeit in a different context. Nonetheless, we prefer to retain the name. :)

Contetnts:

Modules:

• compa.py: A module to make mock observations for COMAP-Y5
• lim.py: The base module for making LIM mocks, e.g. comap.py inherits from this.
• mock_lya.py: A module to make mock observations for the 3D Ly-alpha forest (tomography)
• mock_galaxy: A module to make mock observations for galaxy redshfit surveys
• stats.py: Takes the mock observations as input and calculates the 3D auto and cross power-spectra
• inference.py: Takes the forecast power spectra and runs inference on the paramters for the biased linear power spectra.
• plot.py: A few plotting tools.

helper scripts:

• get_gal.py: Get the mock 3D power spectra for auto CO, galaxy and CO X galaxy.
• get_lya.py: Get the mock 3D power spectra for auto CO, Lya forest and CO X Lya forest.
• get_latis_source_pk.py: Get the projected 2D power spectrum of the sources in LATIS. Note: data used here for LATIS are not publicly available yet, so you can skip this code for now.

Notebooks:

• galaxy_selection.ipynb: Analyzing the HSC photometric obsevration to obtain:

1. The median redshift uncertainties
2. The mass completness with halo abundance matching technique.

• SN_results.ipynb: The results for the forecast S/N ratio of the CO, CO X Lya and CO X Galaxies.
• Inference.ipynb: The results for the inferencee on the biased linear power spectrum parameters.

Data:

All the simulated data will be soon available on Zenodo.