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!

Basics¶

• Reionization & Global 21-cm Signal

  • Two-Zone IGM Model for the Global 21-cm Signal
  • Models with Multiple Source Populations

• 1-D Radiative Transfer

  • RT06 Test #1 (Strömgren Sphere, isothermal)
  • RT06 Test #2 (Strömgren Sphere, thermal evolution allowed)

• Uniform Radiation Backgrounds

  • The Metagalactic UV Background
  • The Metagalactic X-ray Background

Advanced¶

Coming soon. For now, peruse ares/tests/dTb for lots of different 21-cm examples and ares/tests/rt1d for a few more 1-D radiative transfer problems.

Under the hood¶

• Stellar Populations
• Black Hole Populations
• The Intergalactic Medium
• Non-Equilibrium Chemistry Solver

Surveying Parameter Space¶

• Simple Parameter Study
• Advanced Parameter Study
• Analyzing Model Grids
• Running ares with emcee
• Analyzing MCMC Calculations

Post-Processing Cosmological Simulations¶

Stay tuned.

Custom Defaults¶

To adapt the defaults to your liking without modifying the source code (all defaults set in ares.util.SetDefaultParameterValues.py), open the file:

$HOME/.ares/defaults.py

which by default contains nothing:

pf = {}

To craft your own set of defaults, simply add elements to the pf dictionary. For example, if you want to use a default star-formation efficiency of 5% rather than 10%, open $HOME/.ares/defaults.py and do:

pf = {'fstar': 0.05}

That’s it! Elements of pf will override the defaults listed in ares.util.SetDefaultParameterValues.py at run-time.

Alternatively, within a python script you can modify defaults by doing

import ares
ares.rcParams['fstar'] = 0.05

This is similar to how things work in matplotlib (with the matplotlibrc file and matplotlib.rcParams variable).

Custom Axis-Labels¶

You can do the analogous thing for axis labels (all defaults set in ares.util.Aesthetics.py). Open the file:

$HOME/.ares/labels.py

which by default contains nothing:

pf = {}

If you wanted to change the default axis label for the 21-cm brightness temperature, from \(\delta T_b \ (\mathrm{mK})\) to \(T_b\), you would do:

pf = {'dTb': r'$T_b$'}

This change will automatically propagate to all built-in analysis routines.

Species Fractions¶

Our naming convention is to denote ions using their chemical symbol (in lower-case), followed by the ionization state, separated by an underscore. Rather than denoting the ionization state with roman numerals, we simply use integers. For example, neutral hydrogen is h_1 and ionized hydrogen is h_2.

Here is a complete listing:

• Neutral hydrogen fraction: 'h_1'
• Ionized hydrogen fraction: 'h_2'
• Neutral helium fraction: 'he_1'
• Singly-ionized helium fraction: 'he_2'
• Doubly-ionized helium fraction: 'he_3'
• Electron fraction: 'e'
• Gas density (in \(g \ \text{cm}^{-3}\)): 'rho'

These are the default elements in the history dictionary, which is an attribute of all ares.simulations classes.

We also generally keep track of the ionization and heating rate coefficients:

• Rate coefficient for photo-ionization Gamma_h_1.
• etc.

Two-Zone IGM Models¶

For calculations of the reionization history or global 21-cm signal, in which we use a two-zone IGM formalism, all quantities described in the previous sections keep their usual names with one important change: they now also have an igm or cgm prefix to signify which phase of the IGM they belong to. The igm phase is of course short for inter-galactic medium, while the cgm phase stands for the circum-galactic medium (really just meant to indicate gas near galaxies).

• Kinetic temperature, igm_Tk.
• HII region volume filling factor, cgm_h_2.
• Neutral fraction in the bulk IGM, igm_h_1.
• Heating rate in the IGM, igm_heat_h_1.
• Volume-averaged ionization rate, or rate of change in cgm_h_2, cgm_Gamma_h_1.

There are also new (passive) quantities, like the neutral hydrogen excitation (or ``spin’’ temperature), the 21-cm brightness temperature, and rate coefficients that govern the time evolution of the 21-cm signal:

• 21-cm brightness temperature: 'igm_dTb'.
• Spin temperature: 'igm_Ts'.

Each of these are only associated with the IGM grid patch, since the other phase of the IGM is assumed to be fully ionized and thus dark at 21-cm wavelengths.

Plots not showing up¶

If, when running some ares script (e.g., those in $ARES/tests) the program runs to completion without errors but does not produce a figure, it may be due to your matplotlib settings. Most test scripts use draw to ultimately produce the figure because it is non-blocking and thus allows you to continue tinkering with the output if you’d like. One of two things is going on:

• You invoked the script with the standard Python interpreter (i.e., not iPython). Try running it with iPython, which will spit you back into an interactive session once the script is done, and thus keep the plot window open.
• Alternatively, your default matplotlib settings may have caused this. Check out your matplotlibrc file (in $HOME/.matplotlibrc) and make sure interactive : True.

Future versions of ares may use blocking commands to ensure that plot windows don’t disappear immediately. Email me if you have strong opinions about this.

IOError: No such file or directory¶

There are a few different places in the code that will attempt to read-in lookup tables of various sorts. If you get any error that suggests a required input file has not been found, you should:

• Make sure you have set the $ARES environment variable. See the Installation page for instructions.
• Make sure the required file is where it should be, i.e., nested under $ARES/input.

In the event that a required file is missing, something has gone wrong. Many lookup tables are downloaded automatically when you run the setup.py script, so the first thing you should do is re-run python setup.py install.

LinAlgError: singular matrix¶

This is an odd one, known to occur in ares.physics.Hydrogen when using scipy.interpolate.interp1d to compute the collisional coupling coefficients for spin-exchange.

We still aren’t sure why this happens – it cannot always be reproduced, even by two users using the same version of scipy. A temporary hack is to use linear interpolation, instead of a spline, or to hack off data points at high temperatures in the lookup table. Working on a more satisfying solution...email me if you encounter this problem.