CosmoFit.PlanckLensingLikelihood

class CosmoFit.PlanckLensingLikelihood(cosmology, version='planck2018', lens_potential_accuracy=4)

Bases: BaseLikelihood

Planck 2018 lensing-potential bandpowers against a Boltzmann-computed C_L^{phiphi}.

Parameters:

• cosmology – Cosmology model instance. Must be one CAMB can represent (LCDM, or any model with a w(z)); anything else raises BoltzmannError at construction rather than mid-chain.

• version (str, optional) – Dataset version.

• lens_potential_accuracy (int, optional) – CAMB’s lensing accuracy setting. Default 4 here, not the 1 used for the temperature and polarization spectra: this likelihood is the lensing spectrum, and 1 is calibrated for lensing’s effect on TT/TE/EE rather than for the potential itself. The difference is well under the bandpower errors, but it costs little and there is no reason to accept avoidable numerical error in the one quantity being fitted.

Notes

Combining this with "planck" or "planck_lite" is normal and is what Planck’s own analyses do. The lensing reconstruction is built from the same maps as the power spectra, so the two are not strictly independent, but the correlation is small enough that Planck distributes and combines them as separate likelihoods – which is why no conflict is registered for the pair.

__init__(cosmology, version='planck2018', lens_potential_accuracy=4)

Parameters:

• version (str)

• lens_potential_accuracy (int)

Methods

__init__(cosmology[, version, ...])
chi2()	Chi-square statistic.
log_likelihood()	Return log-likelihood.
model()	Predicted lensing bandpowers for the current cosmology.
predictions()	Alias for model().
residuals()	Data minus model bandpower residuals.
summary()	Return a summary of the likelihood evaluation.

Attributes

n_data	Number of data points.
name_and_size	Name together with the number of data points.
observable