Tangos Tutorial – Changa + AHF

Initial set up

Make sure you have followed the initial set up instructions.

Next, download the raw simulation data required for this tutorial. Unpack the tar file either in your home folder or the folder that you pointed the TANGOS_SIMULATION_FOLDER environment variable to.

For most Linux or macOS systems, the following typed at your bash command line will download the required data and unpack it in the correct location:

cd $TANGOS_SIMULATION_FOLDER
curl https://zenodo.org/record/5155467/files/tutorial_changa.tar.gz?download=1 | tar -xz

Import the simulation

At the unix command line type:

tangos add tutorial_changa

The process should take about a minute on a standard modern computer, during which you’ll see a bunch of log messages scroll up the screen.

Let’s pick this command apart

• tangos is the command-line tool to administrate your tangos database
• add is a subcommand to add a new simulation
• tutorial_changa identifies the simulation we’re adding

Note that all tangos command-line tools provide help. For example tangos --help will show you all subcommands, and tangos add --help will tell you more about the possible options for adding a simulation.

At this point, the database knows about the existence of timesteps and their halos in our simulation, but nothing about the properties of those halos or groups. We need to add more information before the database is useful.

If you want to speed up this process, it can be MPI parallelised since version 1.8.

Import some AHF-defined properties

At the unix command line type:

tangos import-properties Mvir Rvir --for tutorial_changa

The process should take less than a minute on a standard modern computer, during which you’ll see a bunch of log messages scroll up the screen.

The example command line lists two properties, Mvir and Rvir to import from the stat files. The added directive --for tutorial_changa specifies which simulation you want to apply this operation to. It’s not strictly necessary to add this if you only have one simulation in your database.

Generate the merger trees

The merger trees are most simply generated using pynbody’s bridge function to do this, type

tangos link --for tutorial_changa

which builds the merger tree for the halos. Again, the --for tutorial_changa may be omitted if it’s the only simulation in your tangos database. Note that in this tutorial, only a few timesteps are provided. This makes the merger trees a little boring (see the Ramses and Gadget tutorial datasets for more interesting merger trees).

The construction of each merger tree should take a few minutes, and again you’ll see a log scroll up the screen while it happens.

If you want to speed up this process, it can be MPI parallelised.

Add the first property

Next, we will add some properties to the halos so that we can start to do some science. Because this is a zoom simulation, we only want to do science on the highest resolution regions. The first thing to calculate is therefore which halos fall in that region. From your shell type:

tangos write contamination_fraction --for tutorial_changa

Here,

• tangos write is the main script for adding properties to a tangos database;
• contamination_fraction is the name of a built-in property which returns the fraction of dark matter particles which come from outside the high resolution region.

If you want to speed up this process, it can be MPI parallelised.

If you want to see how your database is looking, you can skip ahead to data exploration, though so far there’s not a huge amount of interest to see.

Add some more interesting properties

Let’s finally do some science. We’ll add density profiles, thumbnail images, and star formation rates; from your shell type:

tangos write dm_density_profile gas_density_profile uvi_image SFR_histogram --with-prerequisites --include-only="contamination_fraction<0.01" --include-only="NDM()>1000" --for tutorial_changa

Here,

• tangos write is the same script you called above to add properties to the database
• dm_density_profile is an array representing the dark matter density profile; to see all available properties you can call tangos list-possible-properties
• --with-prerequisites automatically includes any underlying properties that are required to perform the calculation. In this case, the dm_density_profile calculation actually needs to know an accurate center for the halo (known as shrink_center), so that calculation will be automatically performed and stored
• --include-only allows an arbitrary filter to be applied, specifying which halos the properties should be calculated for. In the present case, we use that to insist that only “high resolution” halos are included (specifically, those with a fraction of low-res particles smaller than 1%) – and, more than that, there must be 1000 dark matter particles in a halo before we calculate these properties (otherwise it’s too small for us to care).

This is the slowest process in all the tangos tutorials; there is a specific example in the MPI parallelisation document showing how to make best use of a multi-core system to speed things up.

Tangos error handling

While running this case the log may contain some errors such as Number of smoothing particles exceeds number of particles in tree. Don’t panic, this is normal! You’re seeing the effect of attempting to smooth over a very small number of star or gas particles in some tiny halos.

If keen, one can alter the --include-only clause to prevent any such errors occuring but it’s not really necessary: tangos isolates errors that occur in individual halo calculations; it reports them and then moves onto the next calculation or halo.

Explore what’s possible

Now that you have a minimal functioning tangos database, you can proceed to the data exploration tutorial.

However, you can also enable even more functionality by adding a companion simulation which has black hole (AGN) feedback