Properties

The quantities describing global properties of the halos are provided in the data/ directory. Subdirectories are named as follows:

VR{halo-catalogue-id}_{resolution-level}_res_{subgrid-model}/

# halo-catalogue-id: 2915 (group), or 18 (cluster)
# resolution-level: -8 (low-res), or -1 (mid-res), or +8 (high-res, group only)
# subgrid-model: ref (full-physics), or adiabatic (= non-radiative)

Let’s take data/VR2915_+1res_ref/ as an example for the code snippets in this guide.

Data serialisation

This simulation of the group with the Ref SWIFT-EAGLE model contains the following data arrays:

$ ls ./

baryon_mass.npy
bh_edd_fraction.npy
bh_edd_fraction_by_id.npy
bh_mass.npy
bh_mass_by_id.npy
bh_mass_in_50kpc.npy
centre_potential.npy
...

Warning

Object properties are stored in .npy files and serialised with NumPy, which must be installed in your environment. The following I/O functions can be used:

import numpy as np

my_array = np.ones(10)
np.save(my_array, "my_array.npy")

# Load it from file
my_array = np.load(my_array)

In the scripts below, we assume that:

  • You have configured a Python environment

  • The current working directory is the repository’s root directory, entropy-core-evolution/

  • NumPy is imported:

>>> import numpy as np

Example: halo masses

The self-similar masses are stored as arrays in files containing m200 and m500 in their name. In general, the data is stored in a 1D array containing the VR catalogue halo mass for every snapshot in the redshift output list (saved in redshifts.npy). For convenience, commonly used quantities like m200 at \(z=0\) are also duplicated in filenames starting with final_ and containing _0199, which is the index of the final simulation snapshot (out of 200).

>>> m200_z0 = np.load("data/VR2915_+1res_ref/final_m200_0199.npy")
>>> print(m200_z0)  # In solar masses
array(1.81625339e+13)

>>> m500 = np.load("data/VR2915_+1res_ref/m500.npy")
>>> print(m500.shape)  # In solar masses
(200,)
>>> print(m500[-1])
np.float64(8898277215097.906)

These data were used to produce Fig. 1 in the paper.

Example: other self-similar quantities

Similarly to \(M_{500}\), other self-similar quantities can be loaded from data files. A list of available quantities can be found below.

  • r500.npy: the list of virial radii, in Mpc, for the main object at every snapshot.

  • t500.npy: the list of virial temperature, in K, for the main object at every snapshot.

  • k500.npy: the list of virial (self-similar) entropy, in \(kev~cm^2\), for the main

    object at every snapshot.

Example: baryon fractions

The hot (and cold) gas fractions are built from the halo mass, \(M_{500}\), and the hot (and cold) gas mass computed by adding the mass of particles inside \(r_{500}\) with a temperature cut at \(10^5\) K.

>>> m500 = np.load("data/VR2915_+1res_ref/m500.npy")  # In Solar masses
>>> m_hot = np.load("data/VR2915_+1res_ref/hot_gas_mass.npy")  # In Solar masses
>>> hot_gas_fraction = m_hot / m500
>>>
>>> # Return it every 20 snapshots
>>> print(hot_gas_fraction[::20])
array([0.00220512, 0.0002538 , 0.00587353, 0.00801783, 0.01054588,
       0.01692892, 0.02454117, 0.01514342, 0.03016408, 0.03807911])

Similarly, you can compute the other mass ratios used in Fig. 3 from the following files:

  • cold_gas_mass.npy expresses the gas mass inside \(r_{500}\) and below \(10^5\) K.

  • gas_mass.npy expresses the gas mass in Solar masses inside \(r_{500}\) with any

    temperature.

  • star_mass.npy expresses the total stellar mass, in Solar masses, inside \(r_{500}\).

  • baryon_mass.npy expresses the total baryonic mass inside \(r_{500}\), obtained as the

    sum of the total gas and stellar masses above.

Finally, the central black hole mass in Solar masses is given in the bh_mass.npy file.