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.
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:
Be warned: this code is still under active development – use at your own risk! Correctness of results is not guaranteed.
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).
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_ionizationparameter, 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_Salphaparameter, 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
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.
You will need:
If you’d like to build the documentation locally, you’ll need:
Note: ares has been tested only with Python 2.7.x and Python 3.7.x.
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.
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()
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:
Omar Ruiz Macias