extrapolate

Simple log-linear extrapolation of P(k) to high k

File	boltzmann/extrapolate/extrapolate_power.py
Attribution	CosmoSIS Team
URL	https://bitbucket.org/joezuntz/cosmosis

It is sometimes useful to extend matter power spectra P(k) to high values of k. These values are unphysical but are useful for numerical stability.

This module does a simple linear extrapolation in log-log space of P(k) out to a specified kmin and kmax. If the data already extends that far then it does not do anything.

It tries both linear and non-linear spectra but does not complain if either or both are not present.

Assumptions

• Linear extrapolation in log-space of P(k); this is not a great approximation

Setup Parameters

Name	Type	Default	Description
kmax	real		The max wavenumber k to extrapolate to
kmin	real	1.0e10	The min wavenumber k to extrapolate to (default is high enough for no extrapolation)
nmin	int	50	The number of points to add at low k
nmax	int	200	The number of points to add at high k
npoint	int	3	The number of end k-samples to use to fit the slope at the end

Input values

Section	Name	Type	Default	Description
matter_power_lin	z	real 1d		Redshifts of samples
	k_h	real 1d		Inpu k wavenumbers of samples in Mpc/h.
	p_k	real 2d		Matter power spectrum at samples in (Mpc/h)^-3.
matter_power_nl	z	real 1d		Redshifts of samples
	k_h	real 1d		Inpu k wavenumbers of samples in Mpc/h.
	p_k	real 2d		Matter power spectrum at samples in (Mpc/h)^-3.

Output values

Output values

Section	Name	Type	Description
matter_power_lin	z	real 1d	Redshifts of samples
	k_h	real 1d	Inpu k wavenumbers of samples in Mpc/h, extended to kmax
	p_k	real 2d	Matter power spectrum at samples in (Mpc/h)^-3, extended to kmax
matter_power_nl	z	real 1d	Redshifts of samples
	k_h	real 1d	Inpu k wavenumbers of samples in Mpc/h, extended to kmax
	p_k	real 2d	Matter power spectrum at samples in (Mpc/h)^-3, extended to kmax