Potential Correction#

The gravitational-imaging (potential correction) technique: pixelized corrections to the lensing potential, reconstructed alone from an image residual or jointly with the pixelized source by maximising the Bayesian evidence.

Ported from the potential_correction package of Cao et al. 2025 (https://github.com/caoxiaoyue/lensing_potential_correction). If you use this functionality in your research, please cite Cao et al. 2025; citation materials are provided at https://github.com/caoxiaoyue/potential_correction_paper.

`RegularDpsiMesh`	The mesh component of a `DpsiPixelization` model: pixelized potential corrections are defined on a rectangular mesh `factor` times coarser than the data grid.
`PairRegularDpsiMesh`	Pairs the dpsi mesh to the data grid: cleans the data mask, bins it onto the coarser dpsi mesh (cleaning again), builds the bilinear dpsi-to-data interpolation matrix and the sparse first/second derivative operators of both grids.
`DpsiPixelization`	The pixelization of the potential corrections: the dpsi mesh (its coarsening factor) plus the regularization scheme applied to the corrections (`aa.reg.CurvatureMask`, `aa.reg.FourthOrderMask` or a kernel regularization such as `aa.reg.MaternKernel`).
`DpsiSrcPixelization`	The joint pixelization of a source+dpsi inversion: the dpsi pixelization of the potential corrections and the standard autolens pixelization of the source.
`SrcFactory`
`AnalyticSrcFactory`	A source factory evaluating an analytic source galaxy's light profiles directly.
`PixSrcFactoryITP`	A source factory interpolating a pixelized source reconstruction (Delaunay linear interpolation with nearest-neighbour fallback).
`FitDpsiImaging`	A linear inversion of an image residual for pixelized corrections dpsi to the lensing potential, at fixed source: the residual is modelled as -B D_s D_psi dpsi (PSF blur matrix B, source-gradient matrix D_s, dpsi-gradient operator D_psi), regularized on the dpsi mesh and solved for the maximum-evidence correction.
`FitDpsiSrcImaging`	A joint linear inversion of an image for the pixelized source and the pixelized corrections dpsi to the lensing potential, fully accounting for their covariance: the mapping matrix is the horizontal block [F_src \| -B D_s D_psi] and the regularization the block diagonal of the source and dpsi regularization matrices, with the Bayesian evidence used to set both regularization strengths.
`FitDpsiSrcInterferometer`	A joint linear inversion of interferometer visibilities for the pixelized source and the pixelized corrections dpsi to the lensing potential, fully accounting for their covariance.
`IterFitDpsiSrcInterferometer`	Iteratively solves for the pixelized source s and potential corrections dpsi of an interferometer dataset, minimizing the penalized visibility objective with a Levenberg-Marquardt loop on the combined state x = [s \| dpsi].
`DpsiInvAnalysis`	Samples the dpsi pixelization (mesh factor + regularization hyper-parameters) of a dpsi-only inversion of an image residual, with the inversion's Bayesian evidence as the likelihood.
`DpsiSrcInvAnalysis`	Samples the joint source+dpsi pixelization (source pixelization and dpsi mesh/regularization hyper-parameters) of a joint inversion, with the inversion's Bayesian evidence as the likelihood.
`DpsiSrcInvInterferometerAnalysis`	Samples the joint source+dpsi pixelization of a visibility-space joint inversion (`FitDpsiSrcInterferometer`), with the inversion's Bayesian evidence as the likelihood.
`IterDpsiSrcInvInterferometerAnalysis`	Samples the joint source+dpsi pixelization hyper-parameters of the visibility-space iterative LM solver, with its Laplace evidence as the likelihood.