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, or global radiation background calculator.
A few papers on how it works:
- 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)
Plus some more applications:
Be warned: this code is still under active development – use at your own risk! Correctness of results is not guaranteed.
The documentation is still a work in progress.
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. Either way, please provide a link to this page as a footnote.
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:
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.
You will need:
Note: ares has been tested only with Python 2.7.x and Python 3.7.x.
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
If the plot doesn’t appear automatically, set
interactive: True in your matplotlibrc file or type:
import matplotlib.pyplot as pl pl.show()
See the documentation for more examples.
To generate the documentation locally,
cd $ARES/docs make html open _build/html/index.html
pip install sphinx pip install numpydoc pip install nbsphinx
You can also just view the latest build here.
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!
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