ARES

The Accelerated Reionization Era Simulations (ARES) code was designed to rapidly generate models for the global 21-cm signal. It can also be used as a 1-D radiative transfer code, stand-alone non-equilibrium chemistry solver, global radiation background calculator, or semi-analytic galaxy formation model.

The documentation is here.

Technical Details

The main papers that describe how ARES works include:

• 1-D radiative transfer: Mirocha et al. (2012)
• Uniform backgrounds & global 21-cm signal: Mirocha (2014)
• Galaxy luminosity functions: Mirocha, Furlanetto, & Sun (2017)
• Population III star formation: Mirocha et al. (2018)
• Rest-ultraviolet colours at high-z: Mirocha, Mason, & Stark (2020)
• Near-infrared background and nebular emission: Sun et al. (2021)

Plus some more applications:

• Mirocha & Furlanetto (2019)
• Schneider (2018)
• Tauscher et al. (2017)
• Mirocha, Harker, & Burns (2015)

Be warned: this code is still under active development -- use at your own risk! Correctness of results is not guaranteed.

Citation

If you use ARES in paper please reference Mirocha (2014) if it's an application of the global 21-cm modeling machinery and Mirocha et al. (2012) if you use the 1-D radiative transfer and/or SED optimization. For galaxy semi-analytic modeling, please have a look at Mirocha, Furlanetto, & Sun (2017), Mirocha, Mason, & Stark (2020), and Mirocha (2020), and for PopIII star modeling, see Mirocha et al. (2018).

Please also provide a link to this page as a footnote.

Note that for some applications, ARES relies heavily on lookup tables and publicly-available software packages that should be referenced as well. These include:

• Code for Anisotropies in the Microwave Background (CAMB).
• The Halo Mass Function (hmf) package (see Murray et al.(2013)).
• Lookup tables and fitting formulae for the fraction of photo-electron energy deposited in heat, ionization, excitation from Shull & van Steenberg (1985), Ricotti, Gnedin, & Shull (2002), and Furlanetto & Stoever (2010) (see secondary_ionization parameter, values of 2, 3, and 4, respectively).
• Collisional coupling coefficients for the 21-cm line from Zygelman (2005).
• Wouthuysen-Field coupling coefficients for the 21-cm line from Chuzhoy, Alvarez, & Shapiro (2006), Furlanetto & Pritchard (2006), Hirata (2006), and Mittal & Kulkarni (2021) (see approx_Salpha parameter, values of 2, 3, 4, and 5, respectively).
• Lyman-alpha transition probabilities from Pritchard & Furlanetto (2006).
• Stellar population synthesis model options include starburst99 (Leitherer et al. (1999)) and BPASS versions 1 (Eldridge & Stanway (2009)) and 2 (Eldridge et al. (2017),Stanway & Eldridge (2018)) (via pop_sed parameter, values 'starburst99', 'bpass_v1', and 'bpass_v2', respectively).

Feel free to get in touch if you are unsure of whether any of these tools are being used under the hood for your application.

Dependencies

You will need:

• numpy
• scipy
• matplotlib
• h5py

and optionally,

• camb
• hmf
• mpi4py
• pymp
• emcee
• distpy
• progressbar2
• setuptools
• mpmath
• shapely
• descartes

If you'd like to build the documentation locally, you'll need:

• numpydoc
• nbsphinx

and if you'd like to run the test suite locally, you'll want:

• pytest
• pytest-cov

which are pip-installable.

Note: ares has been tested only with Python 2.7.x and Python 3.7.x.

Getting started

To clone a copy and install:

git clone https://github.org/mirochaj/ares.git
cd ares
python setup.py install

ares will look in ares/input for lookup tables of various kinds. To download said lookup tables, run:

python remote.py

This might take a few minutes. If something goes wrong with the download, you can run

python remote.py fresh

to get fresh copies of everything.

Quick Example

To generate a model for the global 21-cm signal, simply type:

import ares

sim = ares.simulations.Global21cm()      # Initialize a simulation object
sim.run()   

You can examine the contents of sim.history, a dictionary which contains the redshift evolution of all IGM physical quantities, or use some built-in analysis routines:

sim.GlobalSignature()

If the plot doesn't appear automatically, set interactive: True in your matplotlibrc file or type:

import matplotlib.pyplot as pl
pl.show()

Help

If you encounter problems with installation or running simple scripts, first check the Troubleshooting page in the documentation to see if you're dealing with a common problem. If you don't find your problem listed there, please let me know!

Contributors

Primary author: Jordan Mirocha (McGill)

Additional contributions / corrections / suggestions from:

• Geraint Harker
• Jason Sun
• Keith Tauscher
• Jacob Jost
• Greg Salvesen
• Adrian Liu
• Saurabh Singh
• Rick Mebane
• Krishma Singal
• Donald Trinh
• Omar Ruiz Macias
• Arnab Chakraborty
• Madhurima Choudhury
• Saul Kohn
• Aurel Schneider
• Kristy Fu
• Garett Lopez
• Ranita Jana
• Daniel Meinert
• Henri Lamarre
• Matteo Leo
• Emma Klemets
• Felix Bilodeau-Chagnon
• Venno Vipp
• Oscar Hernandez
• Joshua Hibbard
• Trey Driskell