Science Score: 54.0%
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Keywords
Repository
Accelerated Reionization Era Simulations
Basic Info
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- Stars: 15
- Watchers: 5
- Forks: 18
- Open Issues: 5
- Releases: 0
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Metadata Files
README.md
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:
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_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
pop_sedparameter, 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:
and optionally,
If you'd like to build the documentation locally, you'll need:
and if you'd like to run the test suite locally, you'll want:
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:
```python 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:
python
sim.GlobalSignature()
If the plot doesn't appear automatically, set interactive: True in your matplotlibrc file or type:
python
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
Owner
- Name: Jordan Mirocha
- Login: mirochaj
- Kind: user
- Location: Pasadena, CA
- Company: Senior NASA Postdoctoral Fellow, Jet Propulsion Laboratory
- Website: https://mirochaj.wixsite.com/home
- Repositories: 14
- Profile: https://github.com/mirochaj
I am an astronomer working at JPL in the area of galaxy formation theory, intensity mapping, and cosmic reionization.
Citation (CITATION)
If you use any of the global 21-cm signal or UV/X-ray radiation background stuff, you should cite:
Mirocha, J., 2014, MNRAS, 443, 1211
@ARTICLE{2014MNRAS.443.1211M,
author = {{Mirocha}, J.},
title = "{Decoding the X-ray properties of pre-reionization era sources}",
journal = {\mnras},
archivePrefix = "arXiv",
eprint = {1406.4120},
keywords = {methods: numerical, dark ages, reionization, first stars, diffuse radiation, X-rays: binaries, X-rays: diffuse background},
year = 2014,
month = sep,
volume = 443,
pages = {1211-1223},
doi = {10.1093/mnras/stu1193},
adsurl = {http://adsabs.harvard.edu/abs/2014MNRAS.443.1211M},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
For the 1-D radiative transfer please cite:
Mirocha, J., Skory, S., Burns, J.O., Wise, J.W., 2012, ApJ, 756, 94
@ARTICLE{2012ApJ...756...94M,
author = {{Mirocha}, J. and {Skory}, S. and {Burns}, J.~O. and {Wise}, J.~H.
},
title = "{Optimized Multi-frequency Spectra for Applications in Radiative Feedback and Cosmological Reionization}",
journal = {\apj},
archivePrefix = "arXiv",
eprint = {1204.1944},
primaryClass = "astro-ph.CO",
keywords = {dark ages, reionization, first stars, methods: numerical, radiative transfer},
year = 2012,
month = sep,
volume = 756,
eid = {94},
pages = {94},
doi = {10.1088/0004-637X/756/1/94},
adsurl = {http://adsabs.harvard.edu/abs/2012ApJ...756...94M},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
For global 21-cm calculations using the UVLF-based model, please cite
@ARTICLE{2017MNRAS.464.1365M,
author = {{Mirocha}, Jordan and {Furlanetto}, Steven R. and {Sun}, Guochao},
title = "{The global 21-cm signal in the context of the high- z galaxy luminosity function}",
journal = {\mnras},
keywords = {galaxies: high-redshift, intergalactic medium, galaxies: luminosity function, mass function, dark ages, reionization, first stars, diffuse radiation, Astrophysics - Astrophysics of Galaxies},
year = 2017,
month = jan,
volume = {464},
number = {2},
pages = {1365-1379},
doi = {10.1093/mnras/stw2412},
archivePrefix = {arXiv},
eprint = {1607.00386},
primaryClass = {astro-ph.GA},
adsurl = {https://ui.adsabs.harvard.edu/abs/2017MNRAS.464.1365M},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
and PopIII star formation
@ARTICLE{2018MNRAS.478.5591M,
author = {{Mirocha}, Jordan and {Mebane}, Richard H. and {Furlanetto}, Steven R. and
{Singal}, Krishma and {Trinh}, Donald},
title = "{Unique signatures of Population III stars in the global 21-cm signal}",
journal = {\mnras},
keywords = {galaxies: high-redshift, intergalactic medium, galaxies: luminosity function, mass function, dark ages, reionization, first stars, diffuse radiation, Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics},
year = 2018,
month = aug,
volume = {478},
number = {4},
pages = {5591-5606},
doi = {10.1093/mnras/sty1388},
archivePrefix = {arXiv},
eprint = {1710.02530},
primaryClass = {astro-ph.GA},
adsurl = {https://ui.adsabs.harvard.edu/abs/2018MNRAS.478.5591M},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
If you use any of the more sophisticated galaxy modeling stuff, e.g., dust reddening, spectral synthesis, please consider citing
@ARTICLE{2020MNRAS.498.2645M,
author = {{Mirocha}, Jordan and {Mason}, Charlotte and {Stark}, Daniel P.},
title = "{Effects of self-consistent rest-ultraviolet colours in semi-empirical galaxy formation models}",
journal = {\mnras},
keywords = {dust, extinction, galaxies: evolution, galaxies: high-redshift, galaxies: ISM, Astrophysics - Astrophysics of Galaxies},
year = 2020,
month = oct,
volume = {498},
number = {2},
pages = {2645-2661},
doi = {10.1093/mnras/staa2586},
archivePrefix = {arXiv},
eprint = {2005.07208},
primaryClass = {astro-ph.GA},
adsurl = {https://ui.adsabs.harvard.edu/abs/2020MNRAS.498.2645M},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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Dependencies
- docutils <0.17
- m2r2 *
- nbsphinx *
- numpydoc *
- sphinx *
- cached_property >=1.5.2<2.0
- camb >=1.3<2.0
- coveralls ==1.11.1
- docutils ==0.17.1
- emcee ==2.2.1
- h5py ==2.9.0
- hmf >=3.1<4.0
- matplotlib ==2.2.4
- numpy ==1.21.0
- pytest ==3.6.4
- pytest-cov ==2.8.1
- pyyaml ==5.4
- scipy ==1.2.1
- actions/checkout v2 composite
- actions/setup-python v2 composite
- codecov/codecov-action v2 composite