halomod.bias.Jing98

class halomod.bias.Jing98(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)

Empirical bias of Jing (1998).

See documentation for Bias for information on input parameters. This model has no free parameters.

Notes

This is an empirical form proposed in [1], with the formula

\[(a/\nu^4 + 1)^{b - c n} \left(1 + \frac{\nu^2 - 1}{\delta_c}\right)\]

The parameters a, b and c are free parameters, with values fitted in [1] of (0.5, 0.06, 0.02), which are the defaults here.

Parameters

• a (float) – The fitting parameters.

• b (float) – The fitting parameters.

• c (float) – The fitting parameters.

References

1(1,2)

Jing, Y. P., “Accurate Fitting Formula for the Two-Point Correlation Function of Dark Matter Halos”, http://adsabs.harvard.edu/abs/1998ApJ…503L…9J, 1998.

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