From 30ad932abec89a23cc7e2ae46e443c5062ae71f1 Mon Sep 17 00:00:00 2001 From: Jammy2211 Date: Thu, 23 Jul 2026 22:58:34 +0100 Subject: [PATCH] docs: link Enzi et al. 2026 (RTU grids) where the rectangular mesh is introduced Chapter 4 tutorial 1 now notes the adaptive rectangular mesh implements the ray-guided transformed uniform (RTU) grid formulation of Enzi et al. 2026 (arXiv:2606.30620), to be cited in published work, and that the regularization differs from the paper's Gaussian-process prior. Notebook regenerated. Part of PyAutoLabs/PyAutoArray#402. Co-Authored-By: Claude Fable 5 Claude-Session: https://claude.ai/code/session_01XK2ZZagTywsBZC4CZL66eB --- .../tutorial_1_pixelizations.ipynb | 10 ++++++++-- .../tutorial_1_pixelizations.py | 10 ++++++++-- 2 files changed, 16 insertions(+), 4 deletions(-) diff --git a/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb b/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb index 521f8be..0c4dbc0 100644 --- a/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb +++ b/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb @@ -117,8 +117,14 @@ "Next, lets set up a `Mesh` using the `mesh` module. The mesh represents the pixel-grid used by the pixelization\n", "to reconstruct the galaxy.\n", "\n", - "There are multiple `Mesh`'s available. For now, we'll keep it simple and use a uniform \n", - "rectangular grid, whose `shape` defines its $(y,x)$ dimensions." + "There are multiple `Mesh`'s available. For now, we'll keep it simple and use a rectangular\n", + "grid, whose `shape` defines its $(y,x)$ dimensions.\n", + "\n", + "The `RectangularAdaptDensity` mesh adapts its pixels to the density of the traced source-plane\n", + "grid via the ray-guided transformed uniform (RTU) grid formulation of Enzi et al. (2026)\n", + "(https://arxiv.org/abs/2606.30620), which should be cited in published work using this mesh.\n", + "Note that whereas that paper pairs the RTU grid with a Gaussian-process source prior,\n", + "**PyAutoLens** instead uses its own regularization schemes, introduced later in this chapter." ] }, { diff --git a/scripts/chapter_4_pixelizations/tutorial_1_pixelizations.py b/scripts/chapter_4_pixelizations/tutorial_1_pixelizations.py index fbad604..230863a 100644 --- a/scripts/chapter_4_pixelizations/tutorial_1_pixelizations.py +++ b/scripts/chapter_4_pixelizations/tutorial_1_pixelizations.py @@ -54,8 +54,14 @@ Next, lets set up a `Mesh` using the `mesh` module. The mesh represents the pixel-grid used by the pixelization to reconstruct the galaxy. -There are multiple `Mesh`'s available. For now, we'll keep it simple and use a uniform -rectangular grid, whose `shape` defines its $(y,x)$ dimensions. +There are multiple `Mesh`'s available. For now, we'll keep it simple and use a rectangular +grid, whose `shape` defines its $(y,x)$ dimensions. + +The `RectangularAdaptDensity` mesh adapts its pixels to the density of the traced source-plane +grid via the ray-guided transformed uniform (RTU) grid formulation of Enzi et al. (2026) +(https://arxiv.org/abs/2606.30620), which should be cited in published work using this mesh. +Note that whereas that paper pairs the RTU grid with a Gaussian-process source prior, +**PyAutoLens** instead uses its own regularization schemes, introduced later in this chapter. """ mesh = al.mesh.RectangularAdaptDensity(shape=(25, 25))