Merge pull request #559 from PyAutoLabs/claude/howtolens-tutorial-restructure-f19y9d

Update RTD howtogalaxy pages for the HowToGalaxy restructure

Author: Jammy2211

docs/howtogalaxy/chapter_2_modeling.md

@@ -1,6 +1,7 @@
 # Chapter 2: Modeling
 
-In chapter 2, we'll take you through how to model galaxies using a non-linear search.
+In chapter 2, we'll take you through how to model galaxies using a non-linear search, ending with how
+searches are chained together into automated modeling pipelines.
 
 The chapter contains the following tutorials:
 
@@ -27,3 +28,9 @@ The chapter contains the following tutorials:
 
 [Tutorial 8: Need for Speed](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_2_modeling/tutorial_8_need_for_speed.ipynb)
 \- How to fit complex models whilst balancing efficiency and run-time.
+
+[Tutorial 9: Search Chaining](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_2_modeling/tutorial_9_search_chaining.ipynb)
+\- Breaking the modeling procedure into a chained sequence of model-fits.
+
+[Tutorial 10: Prior Passing](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_2_modeling/tutorial_10_prior_passing.ipynb)
+\- How the results of earlier searches are passed to later searches.

docs/howtogalaxy/chapter_3_pixelizations.md

@@ -0,0 +1,23 @@
+# Chapter 3: Pixelizations
+
+In chapter 3, we use **Pixelizations** to reconstruct the light of complex galaxies on pixelized grids.
+
+The chapter contains the following tutorials:
+
+[Tutorial 1: Pixelizations](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_3_pixelizations/tutorial_1_pixelizations.ipynb)
+\- Creating a pixel-grid to reconstruct a galaxy's light.
+
+[Tutorial 2: Mappers](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_3_pixelizations/tutorial_2_mappers.ipynb)
+\- How a pixelization maps its pixels to image-pixels.
+
+[Tutorial 3: Inversions](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_3_pixelizations/tutorial_3_inversions.ipynb)
+\- Inverting the mappings to reconstruct the galaxy's light.
+
+[Tutorial 4: Bayesian Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_3_pixelizations/tutorial_4_bayesian_regularization.ipynb)
+\- Smoothing the reconstruction within a Bayesian framework.
+
+[Tutorial 5: Bayesian Formalism](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_3_pixelizations/tutorial_5_bayesian_formalism.ipynb)
+\- The linear algebra and Bayesian evidence equations behind pixelized galaxy reconstruction.
+
+[Tutorial 6: Model Fit](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_3_pixelizations/tutorial_6_model_fit.ipynb)
+\- An example modeling pipeline which uses an inversion.

docs/howtogalaxy/chapter_3_search_chaining.md

@@ -0,0 +1,15 @@
+# Chapter 4: Scaling Up Galaxies
+
+In chapter 4, we scale galaxy modeling up beyond a single galaxy: extra galaxies, blended multi-galaxy
+systems, and cluster fields.
+
+The chapter contains the following tutorials:
+
+[Tutorial 1: Extra Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_4_scaling_up_galaxies/tutorial_1_extra_galaxies.ipynb)
+\- Handling nearby galaxies by scaling their light out of the fit or modeling them explicitly.
+
+[Tutorial 2: Multi Galaxy](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_4_scaling_up_galaxies/tutorial_2_multi_galaxy.ipynb)
+\- Modeling two or more blended galaxies simultaneously and the degeneracies this creates.
+
+[Tutorial 3: Cluster](https://colab.research.google.com/github/PyAutoLabs/HowToGalaxy/blob/2026.8.4.1/notebooks/chapter_4_scaling_up_galaxies/tutorial_3_cluster.ipynb)
+\- Modeling a cluster field's BCG and catalogue-driven member population.

docs/howtogalaxy/chapter_4_pixelizations.md

@@ -6,12 +6,14 @@ The best way to learn **PyAutoGalaxy** is by going through the **HowToGalaxy** l
 repository at [PyAutoLabs/HowToGalaxy](https://github.com/PyAutoLabs/HowToGalaxy).
 
 The lectures are provided as Jupyter notebooks (and Python scripts), and they are linked to via this readthedocs. The
-lectures are composed of five chapters
+lectures are composed of four chapters
 
 - **Introduction** - An introduction to galaxy morphology and structure using **PyAutoGalaxy**.
-- **Lens Modeling** - How to model galaxies, including a primer on Bayesian non-linear analysis.
-- **Search Chaining** - How to fit complex lens models using non-linear search chaining.
-- **Pixelizations** - How to perform pixelized reconstructions of a galaxy.
+- **Modeling** - How to model galaxies, including a primer on Bayesian non-linear analysis and
+  non-linear search chaining.
+- **Pixelizations** - How to perform pixelized reconstructions of a galaxy, including the Bayesian
+  formalism behind them.
+- **Scaling Up Galaxies** - Extra galaxies, blended multi-galaxy systems, and cluster fields.
 
 ## How to Tackle HowToGalaxy
 

docs/howtogalaxy/chapter_4_scaling_up_galaxies.md

@@ -249,8 +249,8 @@ general/credits
 howtogalaxy/howtogalaxy
 howtogalaxy/chapter_1_introduction
 howtogalaxy/chapter_2_modeling
-howtogalaxy/chapter_3_search_chaining
-howtogalaxy/chapter_4_pixelizations
+howtogalaxy/chapter_3_pixelizations
+howtogalaxy/chapter_4_scaling_up_galaxies
 howtogalaxy/chapter_optional
 ```
 

docs/howtogalaxy/howtogalaxy.md

@@ -75,7 +75,7 @@ morphology were already familiar and the statistical techniques used for fitting
 For those less familiar with these concepts (e.g. undergraduate students, new PhD students or interested members of the
 public), things may have been less clear and a slower more detailed explanation of each concept would be beneficial.
 
-The **HowToGalaxy** Jupyter Notebook lectures provide exactly this. They are a 3+ chapter guide which thoroughly
+The **HowToGalaxy** Jupyter Notebook lectures provide exactly this. They are a four-chapter guide which thoroughly
 takes you through the core concepts of galaxy light profiles, teaches you the principles of the statistical
 techniques used in modeling and ultimately will allow you to undertake scientific research like a professional astronomer.