halomod.bias.Seljak04¶
- class halomod.bias.Seljak04(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]¶
Empirical bias relation from Seljak & Warren (2004), without cosmological dependence.
See documentation for
Bias
for information on input parameters. This model has no free parameters.Notes
This the form from [1] without cosmological dependence. The form is
\[a + bx^c + \frac{d}{ex+1} + fx^g\]with \(x = m/m_\star\) (and \(m_star\) the nonlinear mass – see
Bias
for details). The other parameters are all fitted, with values given [1] as(a,b,c,d,e,f,g) = (0.53, 0.39, 0.45, 0.13, 40, 5e-4, 1.5)
.- Parameters
a (float, optional) – The fitted parameters.
b (float, optional) – The fitted parameters.
c (float, optional) – The fitted parameters.
d (float, optional) – The fitted parameters.
e (float, optional) – The fitted parameters.
f (float, optional) – The fitted parameters.
g (float, optional) – The fitted parameters.
References
- 1(1,2)
Seljak, U. and Warren M. S., “Large-scale bias and stochasticity of haloes and dark matter”, https://ui.adsabs.harvard.edu/abs/2004MNRAS.355..129S, 2004.
Methods
__init__
(nu[, delta_c, m, mstar, …])Initialize self.
bias
()Calculate the first-order, linear, deterministic halo bias.
Get a dictionary of all implemented models for this component.
Attributes
The HMF model that pairs with this bias in the peak-background split