Repository navigation
fix: lmp.Gaussian potential from its analytic deflection (correct + ~100x faster) - #681
Merged
Merged
Conversation
…ection The potential decomposed a single Gaussian into 100 Gaussians and was wrong: its gradient did not reproduce the profile's deflections (sign errors for elliptical Gaussians). It is now psi = int_0^1 alpha(t r).r dt over the 20-node Gauss-Legendre rule, using the same in-frame analytic deflection as deflections_2d_via_analytic_from (one Faddeeva call per node). Gradient matches the deflections to 1e-8 and lap(psi) = 2 kappa; a 40-member MGE basis potential on 100x100 drops from >10 min to ~2 s. Closes #680 Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This was referenced Oct 29, 2026
pyautolabs-bot
Bot
removed
the
pending-release
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Closes #680.
What was wrong
lmp.Gaussian.potential_2d_from(and solmp.GaussianGradient, every MGE stellarBasis) decomposed one Gaussian into 100 Gaussians and integrated their deflections. It was slow — a 40-member basis stalled fit visualisation (subplot_tracerpotential panel,tracer.fits) for >10 min on the NumPy path (LensTwin phase 4, Euclid DR1 twins) — and wrong: its finite-difference gradient did not reproduce the profile's own deflections (O(1) differences, sign errors for elliptical Gaussians).Fix
A Gaussian is its own one-term MGE. The potential is now ψ(r) = ∫₀¹ α(t r)·r dt over
MGEDecomposer's 20-node Gauss–Legendre rule, using the same in-frame analytic deflection asdeflections_2d_via_analytic_from(factored into_deflections_in_frame_from, so the two cannot drift). One Faddeeva call per node.Checks
test_gaussian.py.Sersic / Chameleon / cored-Sersic potentials still use the MGE route (correctly — they are not Gaussians); not checked here.
🤖 Generated with Claude Code