Release 2026.8.15.1: bump Colab URL tag refs

Author: rhayes777

notebooks/chapter_1_introduction/README.md

@@ -4,20 +4,20 @@ In chapter 1, we introduce you to strong gravitational lensing and the core **Py
 
 # Files
 
-- [Tutorial 0: Visualization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb) — Setting up **PyAutoLens**'s visualization library.
+- [Tutorial 0: Visualization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb) — Setting up **PyAutoLens**'s visualization library.
 
-- [Tutorial 1: Grids And Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb) — Using grids of (y,x) coordinates with galaxies made up of light profiles.
+- [Tutorial 1: Grids And Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb) — Using grids of (y,x) coordinates with galaxies made up of light profiles.
 
-- [Tutorial 2: Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_1_introduction/tutorial_2_ray_tracing.ipynb) — Using grids, galaxies and mass profiles to perform strong lens ray-tracing.
+- [Tutorial 2: Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_1_introduction/tutorial_2_ray_tracing.ipynb) — Using grids, galaxies and mass profiles to perform strong lens ray-tracing.
 
-- [Tutorial 3: More Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_1_introduction/tutorial_3_more_ray_tracing.ipynb) — Advanced strong lens ray-tracing.
+- [Tutorial 3: More Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_1_introduction/tutorial_3_more_ray_tracing.ipynb) — Advanced strong lens ray-tracing.
 
-- [Tutorial 4: Point Sources](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_1_introduction/tutorial_4_point_sources.ipynb) — How lensing calculations change when the source galaxy is a point source (e.g. a quasar).
+- [Tutorial 4: Point Sources](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_1_introduction/tutorial_4_point_sources.ipynb) — How lensing calculations change when the source galaxy is a point source (e.g. a quasar).
 
-- [Tutorial 5: Lensing Formalism](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_1_introduction/tutorial_5_lensing_formalism.ipynb) — The algebraic lensing formalism used to describe strong lensing.
+- [Tutorial 5: Lensing Formalism](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_1_introduction/tutorial_5_lensing_formalism.ipynb) — The algebraic lensing formalism used to describe strong lensing.
 
-- [Tutorial 6: Data](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_1_introduction/tutorial_6_data.ipynb) — Loading and inspecting telescope imaging data of a strong lens.
+- [Tutorial 6: Data](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_1_introduction/tutorial_6_data.ipynb) — Loading and inspecting telescope imaging data of a strong lens.
 
-- [Tutorial 7: Fitting](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_1_introduction/tutorial_7_fitting.ipynb) — Fitting data with a strong lens model.
+- [Tutorial 7: Fitting](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_1_introduction/tutorial_7_fitting.ipynb) — Fitting data with a strong lens model.
 
-- [Tutorial 8: Summary](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_1_introduction/tutorial_8_summary.ipynb) — A summary of the chapter.
+- [Tutorial 8: Summary](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_1_introduction/tutorial_8_summary.ipynb) — A summary of the chapter.

notebooks/chapter_2_lens_modeling/README.md

@@ -5,24 +5,24 @@ searches are chained together into automated lens modeling pipelines.
 
 # Files
 
-- [Tutorial 1: Non-linear Search](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb) — How a non-linear search is used to fit a lens model and the concepts of a parameter space and priors.
+- [Tutorial 1: Non-linear Search](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb) — How a non-linear search is used to fit a lens model and the concepts of a parameter space and priors.
 
-- [Tutorial 2: Practicalities](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb) — Practicalities of performing model-fitting, like how to inspect the results on your hard-disk.
+- [Tutorial 2: Practicalities](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb) — Practicalities of performing model-fitting, like how to inspect the results on your hard-disk.
 
-- [Tutorial 3: Realism and Complexity](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_3_realism_and_complexity.ipynb) — Finding a balance between realism and complexity when composing and fitting a lens model.
+- [Tutorial 3: Realism and Complexity](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_modeling/tutorial_3_realism_and_complexity.ipynb) — Finding a balance between realism and complexity when composing and fitting a lens model.
 
-- [Tutorial 4: Dealing with Failure](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb) — What to do when PyAutoLens finds an inaccurate lens model.
+- [Tutorial 4: Dealing with Failure](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb) — What to do when PyAutoLens finds an inaccurate lens model.
 
-- [Tutorial 5: Linear Profiles](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb) — Light profiles which capture complex morphologies in a reduced number of non-linear parameters.
+- [Tutorial 5: Linear Profiles](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb) — Light profiles which capture complex morphologies in a reduced number of non-linear parameters.
 
-- [Tutorial 6: Masking and Positions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_6_masking_and_positions.ipynb) — How to mask and mark positions on your data to improve the lens model.
+- [Tutorial 6: Masking and Positions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_modeling/tutorial_6_masking_and_positions.ipynb) — How to mask and mark positions on your data to improve the lens model.
 
-- [Tutorial 7: Results](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_7_results.ipynb) — Overview of the results available after successfully fitting a lens model.
+- [Tutorial 7: Results](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_modeling/tutorial_7_results.ipynb) — Overview of the results available after successfully fitting a lens model.
 
-- [Tutorial 8: Need for Speed](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_8_need_for_speed.ipynb) — How to fit complex models whilst balancing efficiency and run-time.
+- [Tutorial 8: Need for Speed](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_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/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_9_search_chaining.ipynb) — Breaking the lens modeling procedure into a chained sequence of model-fits.
+- [Tutorial 9: Search Chaining](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_modeling/tutorial_9_search_chaining.ipynb) — Breaking the lens modeling procedure into a chained sequence of model-fits.
 
-- [Tutorial 10: Prior Passing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_10_prior_passing.ipynb) — How the results of earlier searches are passed to later searches.
+- [Tutorial 10: Prior Passing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_modeling/tutorial_10_prior_passing.ipynb) — How the results of earlier searches are passed to later searches.
 
-- [Tutorial 11: SLaM](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_2_lens_modeling/tutorial_11_slam.ipynb) — Template pipelines for fitting lens models in standardized ways.
+- [Tutorial 11: SLaM](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_2_lens_modeling/tutorial_11_slam.ipynb) — Template pipelines for fitting lens models in standardized ways.

notebooks/chapter_3_pixelizations/README.md

@@ -4,26 +4,26 @@ In chapter 3, we use **Pixelizations** to reconstruct complex source galaxies on
 
 # Files
 
-- [Tutorial 1: Pixelizations](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_1_pixelizations.ipynb) — Creating a pixel-grid in the source-plane.
+- [Tutorial 1: Pixelizations](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_1_pixelizations.ipynb) — Creating a pixel-grid in the source-plane.
 
-- [Tutorial 2: Mappers](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_2_mappers.ipynb) — How a pixelization maps source-pixels to image-pixels.
+- [Tutorial 2: Mappers](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_2_mappers.ipynb) — How a pixelization maps source-pixels to image-pixels.
 
-- [Tutorial 3: Inversions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_3_inversions.ipynb) — Inverting the mappings to reconstruct the source's light.
+- [Tutorial 3: Inversions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_3_inversions.ipynb) — Inverting the mappings to reconstruct the source's light.
 
-- [Tutorial 4: Bayesian Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_4_bayesian_regularization.ipynb) — Smoothing the source within a Bayesian framework.
+- [Tutorial 4: Bayesian Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_4_bayesian_regularization.ipynb) — Smoothing the source within a Bayesian framework.
 
-- [Tutorial 5: Bayesian Formalism](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_5_bayesian_formalism.ipynb) — The linear algebra and Bayesian evidence equations behind pixelized source reconstruction.
+- [Tutorial 5: Bayesian Formalism](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_5_bayesian_formalism.ipynb) — The linear algebra and Bayesian evidence equations behind pixelized source reconstruction.
 
-- [Tutorial 6: Borders](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_6_borders.ipynb) — Preventing highly demagnified image-pixels ruining the inversion.
+- [Tutorial 6: Borders](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_6_borders.ipynb) — Preventing highly demagnified image-pixels ruining the inversion.
 
-- [Tutorial 7: Lens Modeling](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_7_lens_modeling.ipynb) — How to use inversions to fit a lens model.
+- [Tutorial 7: Lens Modeling](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_7_lens_modeling.ipynb) — How to use inversions to fit a lens model.
 
-- [Tutorial 8: Adaptive Pixelization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_8_adaptive_pixelization.ipynb) — A Delaunay mesh which adapts to the mass model's magnification.
+- [Tutorial 8: Adaptive Pixelization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_8_adaptive_pixelization.ipynb) — A Delaunay mesh which adapts to the mass model's magnification.
 
-- [Tutorial 9: Model Fit](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_9_model_fit.ipynb) — An example lens modeling pipeline which uses an inversion.
+- [Tutorial 9: Model Fit](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_9_model_fit.ipynb) — An example lens modeling pipeline which uses an inversion.
 
-- [Tutorial 10: Fit Problems](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_10_fit_problems.ipynb) — The shortcomings of our lens models and inversions.
+- [Tutorial 10: Fit Problems](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_10_fit_problems.ipynb) — The shortcomings of our lens models and inversions.
 
-- [Tutorial 11: Brightness Adaption](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_11_brightness_adaption.ipynb) — Adapting the pixelization to the source's morphology.
+- [Tutorial 11: Brightness Adaption](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_11_brightness_adaption.ipynb) — Adapting the pixelization to the source's morphology.
 
-- [Tutorial 12: Adaptive Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_3_pixelizations/tutorial_12_adaptive_regularization.ipynb) — Adapting the regularization to the source's morphology.
+- [Tutorial 12: Adaptive Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_3_pixelizations/tutorial_12_adaptive_regularization.ipynb) — Adapting the regularization to the source's morphology.

notebooks/chapter_4_scaling_up_lensing/README.md

@@ -5,14 +5,14 @@ scaling relations, group and cluster scales, and weak lensing.
 
 # Files
 
-- [Tutorial 1: Extra Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_4_scaling_up_lensing/tutorial_1_extra_galaxies.ipynb) — Handling nearby galaxies by scaling their light out of the fit or modeling them explicitly.
+- [Tutorial 1: Extra Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_4_scaling_up_lensing/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/HowToLens/blob/2026.8.14.1/notebooks/chapter_4_scaling_up_lensing/tutorial_2_multi_galaxy.ipynb) — Modeling lenses with two or more co-dominant lens galaxies and the degeneracies this creates.
+- [Tutorial 2: Multi Galaxy](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_4_scaling_up_lensing/tutorial_2_multi_galaxy.ipynb) — Modeling lenses with two or more co-dominant lens galaxies and the degeneracies this creates.
 
-- [Tutorial 3: Scaling Relation](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_4_scaling_up_lensing/tutorial_3_scaling_relation.ipynb) — Tying galaxy masses to their luminosities so model complexity stops growing with each galaxy.
+- [Tutorial 3: Scaling Relation](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_4_scaling_up_lensing/tutorial_3_scaling_relation.ipynb) — Tying galaxy masses to their luminosities so model complexity stops growing with each galaxy.
 
-- [Tutorial 4: Group Scale](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_4_scaling_up_lensing/tutorial_4_group_scale.ipynb) — Modeling group-scale lenses with truncated dPIE members and an optional group dark matter halo.
+- [Tutorial 4: Group Scale](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_4_scaling_up_lensing/tutorial_4_group_scale.ipynb) — Modeling group-scale lenses with truncated dPIE members and an optional group dark matter halo.
 
-- [Tutorial 5: Cluster Scale](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_4_scaling_up_lensing/tutorial_5_cluster_scale.ipynb) — Modeling cluster-scale lenses with point-source positions, the CSV interface and multi-plane ray tracing.
+- [Tutorial 5: Cluster Scale](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_4_scaling_up_lensing/tutorial_5_cluster_scale.ipynb) — Modeling cluster-scale lenses with point-source positions, the CSV interface and multi-plane ray tracing.
 
-- [Tutorial 6: Weak Lensing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.14.1/notebooks/chapter_4_scaling_up_lensing/tutorial_6_weak_lensing.ipynb) — Fitting weak-lensing shear catalogues, which probe mass far beyond the strong lensing region.
+- [Tutorial 6: Weak Lensing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.8.15.1/notebooks/chapter_4_scaling_up_lensing/tutorial_6_weak_lensing.ipynb) — Fitting weak-lensing shear catalogues, which probe mass far beyond the strong lensing region.