gravelamps.likelihood.strong

Gravelamps Strong Lensing Likelihoods

Following are functions handling likelihoods for strong lenisng anslyses

Written by Mick Wright 2023

Classes

JointGWTransient

Implementation of the model specific joint likelihood computation for strongly lensed events

Classes

JointGWTransient

Implementation of the model specific joint likelihood computation for strongly lensed events

Module Contents

class gravelamps.likelihood.strong.JointGWTransient(interferometers_first, interferometers_second, generator_first, generator_second, priors=None)

Bases: bilby.core.likelihood.Likelihood

Implementation of the model specific joint likelihood computation for strongly lensed events

property priors

Prior implementation

noise_log_likelihood()

Compute the noise log likeihood for the two images at the same time

calculate_snrs(waveform_polarisations, interferometer, parameters)

Calculate the SNR for a detector

log_likelihood_image(polarisation, interferometers)

Calculate the contribution to the log likelihood from an individual image

log_likelihood_ratio()

Compute the log likelihood ratio for the two lensed images

log_likelihood()

Compute the log likelihood for the event pair