Quickstart & FAQs#
This page is designed for experienced users who have worked with halo data before and don’t mind a bit of jargon. It also contains FAQs outlining several convenience functions. You can find a more detailed explanation in the Data Access page and in the Data Analysis Tutorial.
First, install/update the Python 3 analysis library, symlib, using pip:
pip install symlib -U
Next, fill out this form to get emailed a user name and password. To download all the Milky Way mass hosts, call the following within Python:
import symlib
symlib.download_files(
"my_user_name", "my_password",
"SymphonyMilkyWay", None, "my/local/directory"
)
The files will be downloaded and unpacked in my/local/directory/SymphonyMilkyWay/HaloXXX
, with a different HaloXXX
directory for each zoom-in host. To load a host’s data into Python, run
r, hist = symlib.read_rockstar("my/local/directory/SymphonyMilkyWay/HaloXXX")
s, hist = symlib.read_symfind("my/local/directory/SymphonyMilkyWay/HaloXXX")
The first line reads in subhalo data accoridng to the Rockstar halo finder and the second according to the Symfind halo finder. Both functions return a pair of similarly formatted arrays: r
and s
are 2D arrays which track the evolution of subhalo properties along the main branches of each of the host’s subhaloes, including disrupted and splashback subhaloes. hist
contains useful annotations on each main branch (e.g. the snapshot of first infall, \(V_{\rm peak}\), etc.) Some subhalos that are clearly artifacts have been removed.
r
and s
are 2D structured numpy arrays which means that multiple values are stored at each element and can be accessed withstrings. The first index goes over subhaloes and the second over snapshots. The first object is the host halo and the remaining are subhlaos sorted by decreasing \(M_{\rm peak}\), down to \(N_{\rm peak} > 300\). For example, r["mvir"][3,200]
gives the mass of of the third largest subhalo during snapshot 200. hist
is a 1D structured array, so hist["mpeak"][3]
gives \(M_{\rm peak}\) for the same subhalo.
A full list of the values in h
can be found here
, and a similar list for hist
can be found by combining this list
and this list
. Units can be found here.
One h
variable requires special note, h["ok"]
, which is true when a subhalo exists and false when it doesn’t exist. For example, if you want to analyze all the subhalos in snapshot 200, you should only analyze halos where h["ok"][:,200]
is true. Symfind does not track subhalos prior to infall.
Below this point are some FAQs about working with this data.
Where can I find example code?#
The tutorial has example code that plots subhalo locations, looks at the mass accretion history of subhalos, and constructs a subhalo mass function from all the hosts in a suite.
How do I loop over all the hosts in a suite?#
symlib.get_host_directory("my/base/directory", "SymphonyMilkyWay", 3)
returns the directory of host 3 in the Milky Way-mass suite. Use a for loop ranging from 0 to symlib.n_hosts("SymphonyMilkyWay")
to access all the directories.
How do I get scale factors?#
symlib.scale_factors("SymphonyMilkyWay")
How do I get simulation parameters?#
param = symlib.simulation_parameters("path/to/HaloXXX")
params
is a dictionary with various cosmological and numerical parameters
{'flat': True, 'H0': 70.0, 'Om0': 0.286, 'Ob0': 0.049,
'sigma8': 0.82, 'ns': 0.95, 'eps': 0.17, 'mp': 281981.0,
'h100': 0.7}
Note that eps
is in comoving \(h^{-1}\,{\rm kpc}\) and mp
is in \(h^{-1}M_\odot\).
How do I get halo properties in comoving units?#
h, hist = symlib.read_subhalos("path/to/HaloXXX", comoving=True)
How do I get halos/properties not included in the “halos” dataset?#
The default “halos” dataset (i.e. the data read in by symlib.read_subhalos()
) contains the main branches of every object that has ever been a subhalo of the host as long as the three following conditions are met:
\(N_{\rm peak} > 300\), where \(N_{\rm peak}\) is measured prior to the subhalo’s first infall. First infall includes halos other than the host and does not include temporary Rockstar errors caused by major mergers.
The halo is not a subhalo during its first snapshot.
If the halo disrupts, consistent-trees merges it with any other halo.
If you want other objects, you will need to analyze the full merger tree. This must be downloaded separately. Symphony’s merger trees use a different format than consistent-trees, so it would be best to read through the full tutorial. The full merger tree also contains additional variables <merger_tree_variables> not included in the standard halo dataset.