LIMpy

A python package for multi-line intensity mapping

Description

LIMpy package is useful to model and alayze multi line intensity maps of CII (158 $\mu m$), OIII (88 $\mu m$), and CO (1-0) to CO (13-12) transitions. This code can be used for following things:

• Analytic model for star formation rate
• Multi-line luminosity models
• Multi line intensity power spectrum based on Halo model approach
• Simulate line intensity maps based on halo catalogs
• Calculate power spectrum from simulated maps in cube and rectangular box
• Calculate cross-correlated signal between two separate lines
• Apply Gaussian beam convolution
• Can be used to quantify interlopers, signal-to-noise ratio, etc.

Requirements

This code uses mainly three external packages:

• CAMB: Used to calculate the matter power spectrum.
• Colossus: used mainly to calculate halo mass function.
• Astropy: used to implement beam convolution.

Installation

You can install LIMpy by cloning the package directly from GitHub. git clone https://github.com/Anirbancosmo/Limpy.git cd Limpy python setup.py install

Initialization

Set the default cosmological and Astrophysical parameters in input.py file. These parameters will be used to fix the halo mass function,

Examples

See my examples folder for a quick start.

Luminosity_and_sfr : Check the available models for star formation rate and line luminosities.

Powerspectra-halo-model.ipynb: examples that show how to calculate line intensity power spectra based on halo model approach.

Simulated_maps_and_powerspectra.ipynb: some examples that show how to paint various line intensities on an external halo catalogue.

Citation

If you find this package (or the paper) helpful in your research, please cite the following paper: Arxiv:2304.06748.

@article{Roy:2023cpx,
author = "Roy, Anirban and Valent\'\i{}n-Mart\'\i{}nez, Dariannette and Wang, Kailai and Battaglia, Nicholas and van Engelen, Alexander",
title = "{$\texttt{LIMpy}$: A Semi-analytic Approach to Simulating Multi-line Intensity Maps at Millimetre Wavelengths}",
eprint = "2304.06748",
archivePrefix = "arXiv",
primaryClass = "astro-ph.GA",
month = "4",
year = "2023"}

Contact

Anirban Roy (ar689@cornell.edu)