class halotools.empirical_models.ZuMandelbaum15Sats(threshold=10.5, prim_haloprop_key='halo_m200m', **kwargs)[source] [edit on github]

Bases: halotools.empirical_models.OccupationComponent

HOD-style model for a satellite galaxy occupation based on Zu & Mandelbaum 2015.


The ZuMandelbaum15Sats model is part of the zu_mandelbaum15 prebuilt composite HOD-style model. For a tutorial on the zu_mandelbaum15 composite model, see Zu & Mandelbaum et al. (2015) Composite Model.


threshold : float, optional

Stellar mass threshold of the mock galaxy sample in h=1 solar mass units. Default value is specified in the model_defaults module.

prim_haloprop_key : string, optional

String giving the column name of the primary halo property governing the occupation statistics of gal_type galaxies. Default value is specified in the model_defaults module.


Note also that the best-fit parameters of this model are based on the halo_m200m halo mass definition. Using alternative choices of mass definition will require altering the model parameters in order to mock up the same model published in Zu & Mandelbaum 2015. The Colossus python package written by Benedikt Diemer can be used to convert between different halo mass definitions. This may be useful if you wish to use an existing halo catalog for which the halo mass definition you need is unavailable.


>>> sat_model = ZuMandelbaum15Sats()
>>> sat_model = ZuMandelbaum15Sats(threshold=11)
>>> sat_model = ZuMandelbaum15Sats(prim_haloprop_key='halo_mvir')

Methods Summary

mean_occupation(**kwargs) Expected number of satellite galaxies in a halo of mass halo_mass.

Methods Documentation

mean_occupation(**kwargs)[source] [edit on github]

Expected number of satellite galaxies in a halo of mass halo_mass.


prim_haloprop : array, optional

array of masses of table in the catalog

table : object, optional

Data table storing halo catalog.


mean_nsat : array

Mean number of satellite galaxies in the halo of the input mass.


>>> sat_model = ZuMandelbaum15Sats()
>>> halo_masses = np.logspace(11, 15, 25)
>>> mean_nsat = sat_model.mean_occupation(prim_haloprop=halo_masses)