halomod.bias.Bias

class halomod.bias.Bias(nu: numpy.ndarray, delta_c: float = 1.686, m: Optional[numpy.ndarray] = None, mstar: Optional[float] = None, delta_halo: Optional[float] = 200, n: Optional[float] = 1, sigma_8: Optional[float] = 0.8, cosmo: astropy.cosmology.core.FLRW = FlatLambdaCDM(name="Planck15", H0=67.7 km / (Mpc s), Om0=0.307, Tcmb0=2.725 K, Neff=3.05, m_nu=[0.   0.   0.06] eV, Ob0=0.0486), n_eff: Optional[numpy.ndarray] = None, z: float = 0.0, **model_parameters)[source]

The base Bias component.

This class should not be instantiated directly! Use a subclass that implements a specific bias model. The parameters listed below are the input parameters for all bias models. Extra model-specific parameters can be given – these are documented in their respective class docstring.

Parameters

  • nu (array-like) – Peak-height, delta^2_c/sigma^2.

  • delta_c (float, optional) – Critical over-density for collapse. Not all bias components require this parameter.

  • m (array, optional) – Vector of halo masses corresponding to nu. Not all bias components require this parameter.

  • mstar (float, optional) – Nonlinear mass, defined by the relation sigma(mstar) = delta_c, with sigma the mass variance in spheres corresponding to virial radii of halos of mass mstar.

  • delta_halo (float, optional) – The over-density of halos with respect to the mean background matter density.

  • n (float, optional) – The spectral index of the linear matter power spectrum..

  • Om0 (float, optional) – The matter density, as a fraction of critical density, in the current universe.

  • sigma_8 (float, optional) – The square root of the mass in spheres of radius 8 Mpc/h in the present day (normalizes the power spectrum).

  • h (float, optional) – Hubble parameter in units of 100 km/s/Mpc.

Methods

__init__(nu[, delta_c, m, mstar, …])

Initialize self.

bias()

Calculate the first-order, linear, deterministic halo bias.

get_models()

Get a dictionary of all implemented models for this component.

Attributes

pair_hmf

The HMF model that pairs with this bias in the peak-background split