dsf.data_vector.mag_bias module

Lens-magnification correction for Delta Sigma calculations.

This module computes the correction to the comoving excess surface density profile caused by magnification of the lens sample. The correction is evaluated using a nested integral over foreground redshift and multipole.

The public function delta_sigma_lens_mag_correction returns the quantity that should be subtracted from the observed Delta Sigma signal when including lens magnification.

dsf.data_vector.mag_bias.delta_sigma_lens_mag_correction(r, a_lens, a_source, cosmo, alpha_lens)[source]

Compute the lens-magnification correction to Delta Sigma.

This returns the comoving correction to the excess surface density profile caused by magnification of the lens sample. The correction is evaluated at lens scale factor a_lens, source scale factor a_source, and projected comoving radii r.

The returned correction has the same radial shape as r and is intended to be subtracted from the measured Delta Sigma signal.

Parameters:

  • r (ndarray[tuple[Any, ...], dtype[float64]]) – Comoving projected radii in Mpc.

  • a_lens (float) – Lens scale factor.

  • a_source (float) – Source scale factor.

  • cosmo (Cosmology) – CCL cosmology object.

  • alpha_lens (float) – Lens-sample magnification-bias slope. The correction is proportional to alpha_lens - 1.

Returns:

Comoving lens-magnification correction in \(M_\odot / \mathrm{pc}^2\).

Raises:

  • ValueError – If the radius array, lens scale factor, source scale factor,

  • lens magnification-bias slope, or derived lens/source redshift pair is invalid. –

Return type:

ndarray[tuple[Any, …], dtype[float64]]

dsf.data_vector.mag_bias.get_lens_mag_integ_params()[source]

Return the lens-magnification integration parameters.

Returns:

Copy of the current lens-magnification integration parameter dictionary.

Return type:

dict[str, int | float]

dsf.data_vector.mag_bias.set_lens_mag_integ_params(**kwargs)[source]

Update the lens-magnification integration parameters.

Parameters:

**kwargs (Any) – Integration parameters to update. Supported keys are n_ell, ell_min, ell_max, z_stepsize, z_min, and use_hankel_offset. use_hankel_offset applies an offset to the logarithmic spacing of the output, which can reduce numerical ringing at the cost of some accuracy.

Raises:

  • KeyError – If an unknown integration parameter is supplied.

  • ValueError – If the updated integration parameters are invalid.

Return type:

None