diff --git a/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb b/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb
index ed5359d..ba30f7d 100644
--- a/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb
+++ b/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb
@@ -1104,7 +1104,7 @@
     "adaptive over sampling scheme with high accuracy across all use cases.\n",
     "\n",
     "Once you are more experienced, you should read up on over-sampling in more detail via\n",
-    "the `autolens_workspace/*/guides/over_sampling.ipynb` notebook."
+    "the `autolens_workspace/*/guides/advanced/over_sampling.ipynb` notebook."
    ]
   }
  ],
diff --git a/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb
index 49c490a..c4c2fb4 100644
--- a/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb
+++ b/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb
@@ -521,7 +521,7 @@
     "fitted the data.\n",
     "\n",
     "A detailed step-by-step visual guide of the likelihood function is provided \n",
-    "at `autolens_workspace/*/imaging/log_likelihood_function/parametric.ipynb`."
+    "at `autolens_workspace/*/imaging/likelihood_function.ipynb`."
    ]
   },
   {
diff --git a/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb
index ebb335d..8952443 100644
--- a/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb
+++ b/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb
@@ -384,11 +384,11 @@
     "limiting, as the notebook cell will only complete once the fit finishes, preventing you from advancing through the \n",
     "tutorial or running additional code.\n",
     "\n",
-    "To work around this, we recommend running tutorial scripts as standalone Python scripts, found \n",
-    "in `autolens_workspace/scripts/howtogalaxy`. These scripts mirror the notebook tutorials but run independently of \n",
+    "To work around this, we recommend running tutorial scripts as standalone Python scripts, found\n",
+    "in the `scripts/` folder of the HowToLens repository. These scripts mirror the notebook tutorials but run independently of\n",
     "Jupyter notebooks. For example, you can start a script with:\n",
     "\n",
-    "`python3 scripts/howtogalaxy/chapter_2_modeling/tutorial_2_practicalities.py`\n",
+    "`python3 scripts/chapter_2_lens_modeling/tutorial_2_practicalities.py`\n",
     "\n",
     "Using scripts allows results to be saved to the hard drive in the `output` folder, enabling you to inspect results \n",
     "immediately once the script completes. When rerun, the script loads results directly from disk, so any Jupyter \n",
diff --git a/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb
index 8b6f091..4ada2d5 100644
--- a/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb
+++ b/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb
@@ -708,7 +708,7 @@
     "find the global maximum lens model. However, this also means the search will take longer!\n",
     "\n",
     "Below, we configure a more thorough Nautilus search with `n_live=200`. These settings and what they change are \n",
-    "discussed in the optional tutorial `howtolens/chapter_optional/tutorial_searches.ipynb`.\n",
+    "discussed in the optional tutorial `chapter_optional/tutorial_searches.ipynb`.\n",
     "\n",
     "Due to the long run times of this search, the output is commented out below. Feel free to uncomment it to run the \n",
     "script faster."
diff --git a/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb b/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb
index 4af947a..e068271 100644
--- a/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb
+++ b/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb
@@ -801,7 +801,7 @@
     "in a much simpler non-linear parameter space which has far less significant parameter degeneracies!\n",
     "\n",
     "We strongly recommend that you adopt an MGE in your own lens modeling pipelines from here on. The script \n",
-    "`autolens_workspace/*/modeling/features/multi_gaussian_expansion.py` gives examples on fitting even more complex\n",
+    "`autolens_workspace/*/imaging/features/multi_gaussian_expansion/modeling.py` gives examples on fitting even more complex\n",
     "MGE models, where for example the Gaussians have different axis-ratios and position angles.\n",
     "\n",
     "__Disadvantage of Basis Functions__\n",
@@ -833,7 +833,7 @@
     "features of a galaxy. They do so over a wide range of scales, and can often represent  features in source galaxies \n",
     "that a single Sersic function or MGE cannot.\n",
     "\n",
-    "An example using shapelets is given at `autolens_workspace/scripts/modeling/features/shapelets.py`.\n",
+    "An example using shapelets is given at `autolens_workspace/scripts/imaging/features/advanced/shapelets/modeling.py`.\n",
     " \n",
     "Feel free to experiment with using shapelets as the source galaxy by yourself. However they incur higher computational \n",
     "overheads than the MGE and include a free parameter which governs the size of the basis functions and therefore source,\n",
diff --git a/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb b/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb
index a399b40..39df2b6 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb
@@ -512,7 +512,7 @@
     "__Detailed Explanation__\n",
     "\n",
     "If you are interested in a more detailed description of how inversions work, then checkout the file\n",
-    "`autolens_workspace/*/imaging/log_likelihood_function/inversion.ipynb` which gives a visual step-by-step\n",
+    "`autolens_workspace/*/imaging/features/pixelization/likelihood_function.ipynb` which gives a visual step-by-step\n",
     "guide of the process alongside equations and references to literature on the subject."
    ]
   }
diff --git a/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb b/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb
index b7495f3..dc54f84 100644
--- a/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb
+++ b/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb
@@ -9,7 +9,7 @@
     "\n",
     "You should now perform lens modeling using a pixelization, which is described fully in the example:\n",
     "\n",
-    "`autolens_workspace/*/imaging/features/pixelizations/modeling.py`\n",
+    "`autolens_workspace/*/imaging/features/pixelization/modeling.py`\n",
     "\n",
     "__Wrap Up__\n",
     "\n",
diff --git a/notebooks/simulator/lens_sersic.ipynb b/notebooks/simulator/lens_sersic.ipynb
index 792504f..e1451cd 100644
--- a/notebooks/simulator/lens_sersic.ipynb
+++ b/notebooks/simulator/lens_sersic.ipynb
@@ -32,7 +32,7 @@
     "\n",
     "__Start Here Notebook__\n",
     "\n",
-    "If any code in this script is unclear, refer to the `simulators/start_here.ipynb` notebook."
+    "If any code in this script is unclear, refer to the `autolens_workspace/*/imaging/simulator.ipynb` notebook."
    ]
   },
   {
diff --git a/notebooks/simulator/lens_x2.ipynb b/notebooks/simulator/lens_x2.ipynb
index 8f5df08..409a5a8 100644
--- a/notebooks/simulator/lens_x2.ipynb
+++ b/notebooks/simulator/lens_x2.ipynb
@@ -40,7 +40,7 @@
     "\n",
     "__Start Here Notebook__\n",
     "\n",
-    "If any code in this script is unclear, refer to the `simulators/start_here.ipynb` notebook."
+    "If any code in this script is unclear, refer to the `autolens_workspace/*/imaging/simulator.ipynb` notebook."
    ]
   },
   {
diff --git a/notebooks/simulator/no_lens_light.ipynb b/notebooks/simulator/no_lens_light.ipynb
index 6b036f5..d9de134 100644
--- a/notebooks/simulator/no_lens_light.ipynb
+++ b/notebooks/simulator/no_lens_light.ipynb
@@ -10,7 +10,7 @@
     "This script simulates `Imaging` of a 'galaxy-scale' which is identical to the `simple` simulated in the `start_here.py`\n",
     "script, but where the lens galaxy's light is omitted.\n",
     "\n",
-    "It is used in `autolens_workspace/notebooks/modeling/features/no_lens_light.ipynb` to illustrate how to fit a\n",
+    "It is used in `autolens_workspace/notebooks/imaging/features/no_lens_light/modeling.ipynb` to illustrate how to fit a\n",
     "lens model to data where the lens galaxy's light is not present (e.g. because it is too faint to be detected).\n",
     "\n",
     "__Contents__\n",
@@ -33,7 +33,7 @@
     "\n",
     "__Start Here Notebook__\n",
     "\n",
-    "If any code in this script is unclear, refer to the `simulators/start_here.ipynb` notebook."
+    "If any code in this script is unclear, refer to the `autolens_workspace/*/imaging/simulator.ipynb` notebook."
    ]
   },
   {
@@ -340,7 +340,8 @@
     "__Mask Extra Galaxies__\n",
     "\n",
     "This dataset has no extra galaxies, but pixelization tutorials that load it (e.g.\n",
-    "`imaging/features/pixelization/modeling.py`, `imaging/features/pixelization/fit.py`) demonstrate the\n",
+    "`autolens_workspace/scripts/imaging/features/pixelization/modeling.py`,\n",
+    "`autolens_workspace/scripts/imaging/features/pixelization/fit.py`) demonstrate the\n",
     "noise-scaling API by applying a `mask_extra_galaxies` mask to the dataset. Output an empty (all-False,\n",
     "no-pixels-masked) mask so those tutorials can call `apply_noise_scaling(mask=...)` without crashing on a\n",
     "missing FITS file. The mask shape tracks `dataset.shape_native`, so `PYAUTO_SMALL_DATASETS=1` is honoured\n",
diff --git a/notebooks/simulator/no_lens_light__mass_sis.ipynb b/notebooks/simulator/no_lens_light__mass_sis.ipynb
index edb0cfc..6fbe806 100644
--- a/notebooks/simulator/no_lens_light__mass_sis.ipynb
+++ b/notebooks/simulator/no_lens_light__mass_sis.ipynb
@@ -31,7 +31,7 @@
     "\n",
     "__Start Here Notebook__\n",
     "\n",
-    "If any code in this script is unclear, refer to the `simulators/start_here.ipynb` notebook."
+    "If any code in this script is unclear, refer to the `autolens_workspace/*/imaging/simulator.ipynb` notebook."
    ]
   },
   {
diff --git a/notebooks/simulator/source_complex.ipynb b/notebooks/simulator/source_complex.ipynb
index eb9555c..8cc805f 100644
--- a/notebooks/simulator/source_complex.ipynb
+++ b/notebooks/simulator/source_complex.ipynb
@@ -35,7 +35,7 @@
     "\n",
     "__Start Here Notebook__\n",
     "\n",
-    "If any code in this script is unclear, refer to the `simulators/start_here.ipynb` notebook."
+    "If any code in this script is unclear, refer to the `autolens_workspace/*/imaging/simulator.ipynb` notebook."
    ]
   },
   {
diff --git a/scripts/chapter_1_introduction/tutorial_1_grids_and_galaxies.py b/scripts/chapter_1_introduction/tutorial_1_grids_and_galaxies.py
index 52c203e..56cada6 100644
--- a/scripts/chapter_1_introduction/tutorial_1_grids_and_galaxies.py
+++ b/scripts/chapter_1_introduction/tutorial_1_grids_and_galaxies.py
@@ -668,5 +668,5 @@
 adaptive over sampling scheme with high accuracy across all use cases.
 
 Once you are more experienced, you should read up on over-sampling in more detail via
-the `autolens_workspace/*/guides/over_sampling.ipynb` notebook.
+the `autolens_workspace/*/guides/advanced/over_sampling.ipynb` notebook.
 """
diff --git a/scripts/chapter_2_lens_modeling/tutorial_1_non_linear_search.py b/scripts/chapter_2_lens_modeling/tutorial_1_non_linear_search.py
index 0920b77..9f28674 100644
--- a/scripts/chapter_2_lens_modeling/tutorial_1_non_linear_search.py
+++ b/scripts/chapter_2_lens_modeling/tutorial_1_non_linear_search.py
@@ -357,7 +357,7 @@
 fitted the data.
 
 A detailed step-by-step visual guide of the likelihood function is provided 
-at `autolens_workspace/*/imaging/log_likelihood_function/parametric.ipynb`.
+at `autolens_workspace/*/imaging/likelihood_function.ipynb`.
 """
 analysis = al.AnalysisImaging(dataset=dataset)
 
diff --git a/scripts/chapter_2_lens_modeling/tutorial_2_practicalities.py b/scripts/chapter_2_lens_modeling/tutorial_2_practicalities.py
index 68a6da9..c0cbdf3 100755
--- a/scripts/chapter_2_lens_modeling/tutorial_2_practicalities.py
+++ b/scripts/chapter_2_lens_modeling/tutorial_2_practicalities.py
@@ -253,11 +253,11 @@
 limiting, as the notebook cell will only complete once the fit finishes, preventing you from advancing through the 
 tutorial or running additional code.
 
-To work around this, we recommend running tutorial scripts as standalone Python scripts, found 
-in `autolens_workspace/scripts/howtogalaxy`. These scripts mirror the notebook tutorials but run independently of 
+To work around this, we recommend running tutorial scripts as standalone Python scripts, found
+in the `scripts/` folder of the HowToLens repository. These scripts mirror the notebook tutorials but run independently of
 Jupyter notebooks. For example, you can start a script with:
 
-`python3 scripts/howtogalaxy/chapter_2_modeling/tutorial_2_practicalities.py`
+`python3 scripts/chapter_2_lens_modeling/tutorial_2_practicalities.py`
 
 Using scripts allows results to be saved to the hard drive in the `output` folder, enabling you to inspect results 
 immediately once the script completes. When rerun, the script loads results directly from disk, so any Jupyter 
diff --git a/scripts/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.py b/scripts/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.py
index ff06247..5837756 100644
--- a/scripts/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.py
+++ b/scripts/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.py
@@ -402,7 +402,7 @@
 find the global maximum lens model. However, this also means the search will take longer!
 
 Below, we configure a more thorough Nautilus search with `n_live=200`. These settings and what they change are 
-discussed in the optional tutorial `howtolens/chapter_optional/tutorial_searches.ipynb`.
+discussed in the optional tutorial `chapter_optional/tutorial_searches.ipynb`.
 
 Due to the long run times of this search, the output is commented out below. Feel free to uncomment it to run the 
 script faster.
diff --git a/scripts/chapter_2_lens_modeling/tutorial_5_linear_profiles.py b/scripts/chapter_2_lens_modeling/tutorial_5_linear_profiles.py
index c96e6de..25be59d 100644
--- a/scripts/chapter_2_lens_modeling/tutorial_5_linear_profiles.py
+++ b/scripts/chapter_2_lens_modeling/tutorial_5_linear_profiles.py
@@ -496,7 +496,7 @@
 in a much simpler non-linear parameter space which has far less significant parameter degeneracies!
 
 We strongly recommend that you adopt an MGE in your own lens modeling pipelines from here on. The script 
-`autolens_workspace/*/modeling/features/multi_gaussian_expansion.py` gives examples on fitting even more complex
+`autolens_workspace/*/imaging/features/multi_gaussian_expansion/modeling.py` gives examples on fitting even more complex
 MGE models, where for example the Gaussians have different axis-ratios and position angles.
 
 __Disadvantage of Basis Functions__
@@ -528,7 +528,7 @@
 features of a galaxy. They do so over a wide range of scales, and can often represent  features in source galaxies 
 that a single Sersic function or MGE cannot.
 
-An example using shapelets is given at `autolens_workspace/scripts/modeling/features/shapelets.py`.
+An example using shapelets is given at `autolens_workspace/scripts/imaging/features/advanced/shapelets/modeling.py`.
  
 Feel free to experiment with using shapelets as the source galaxy by yourself. However they incur higher computational 
 overheads than the MGE and include a free parameter which governs the size of the basis functions and therefore source,
diff --git a/scripts/chapter_4_pixelizations/tutorial_3_inversions.py b/scripts/chapter_4_pixelizations/tutorial_3_inversions.py
index 3557df4..5e18954 100644
--- a/scripts/chapter_4_pixelizations/tutorial_3_inversions.py
+++ b/scripts/chapter_4_pixelizations/tutorial_3_inversions.py
@@ -305,6 +305,6 @@
 __Detailed Explanation__
 
 If you are interested in a more detailed description of how inversions work, then checkout the file
-`autolens_workspace/*/imaging/log_likelihood_function/inversion.ipynb` which gives a visual step-by-step
+`autolens_workspace/*/imaging/features/pixelization/likelihood_function.ipynb` which gives a visual step-by-step
 guide of the process alongside equations and references to literature on the subject.
 """
diff --git a/scripts/chapter_4_pixelizations/tutorial_8_model_fit.py b/scripts/chapter_4_pixelizations/tutorial_8_model_fit.py
index 4519f71..6d02e54 100755
--- a/scripts/chapter_4_pixelizations/tutorial_8_model_fit.py
+++ b/scripts/chapter_4_pixelizations/tutorial_8_model_fit.py
@@ -1,13 +1,13 @@
-"""
-Tutorial 8: Model-Fit
-=====================
-
-You should now perform lens modeling using a pixelization, which is described fully in the example:
-
-`autolens_workspace/*/imaging/features/pixelizations/modeling.py`
-
-__Wrap Up__
-
-Once complete, you can then move on to the next HowToLens tutorial and gain more insight into adaptive
-pixelizations.
-"""
+"""
+Tutorial 8: Model-Fit
+=====================
+
+You should now perform lens modeling using a pixelization, which is described fully in the example:
+
+`autolens_workspace/*/imaging/features/pixelization/modeling.py`
+
+__Wrap Up__
+
+Once complete, you can then move on to the next HowToLens tutorial and gain more insight into adaptive
+pixelizations.
+"""
diff --git a/scripts/simulator/lens_sersic.py b/scripts/simulator/lens_sersic.py
index 8a4cf58..e32c962 100644
--- a/scripts/simulator/lens_sersic.py
+++ b/scripts/simulator/lens_sersic.py
@@ -27,7 +27,7 @@
 
 __Start Here Notebook__
 
-If any code in this script is unclear, refer to the `simulators/start_here.ipynb` notebook.
+If any code in this script is unclear, refer to the `autolens_workspace/*/imaging/simulator.ipynb` notebook.
 """
 
 from autolens import jax_wrapper  # Sets JAX environment before other imports
diff --git a/scripts/simulator/lens_x2.py b/scripts/simulator/lens_x2.py
index fb93dbe..0a34fed 100644
--- a/scripts/simulator/lens_x2.py
+++ b/scripts/simulator/lens_x2.py
@@ -35,7 +35,7 @@
 
 __Start Here Notebook__
 
-If any code in this script is unclear, refer to the `simulators/start_here.ipynb` notebook.
+If any code in this script is unclear, refer to the `autolens_workspace/*/imaging/simulator.ipynb` notebook.
 """
 
 from pathlib import Path
diff --git a/scripts/simulator/no_lens_light.py b/scripts/simulator/no_lens_light.py
index 2d3d052..3592d03 100644
--- a/scripts/simulator/no_lens_light.py
+++ b/scripts/simulator/no_lens_light.py
@@ -5,7 +5,7 @@
 This script simulates `Imaging` of a 'galaxy-scale' which is identical to the `simple` simulated in the `start_here.py`
 script, but where the lens galaxy's light is omitted.
 
-It is used in `autolens_workspace/notebooks/modeling/features/no_lens_light.ipynb` to illustrate how to fit a
+It is used in `autolens_workspace/notebooks/imaging/features/no_lens_light/modeling.ipynb` to illustrate how to fit a
 lens model to data where the lens galaxy's light is not present (e.g. because it is too faint to be detected).
 
 __Contents__
@@ -28,7 +28,7 @@
 
 __Start Here Notebook__
 
-If any code in this script is unclear, refer to the `simulators/start_here.ipynb` notebook.
+If any code in this script is unclear, refer to the `autolens_workspace/*/imaging/simulator.ipynb` notebook.
 """
 
 from autolens import jax_wrapper  # Sets JAX environment before other imports
@@ -165,7 +165,8 @@
 __Mask Extra Galaxies__
 
 This dataset has no extra galaxies, but pixelization tutorials that load it (e.g.
-`imaging/features/pixelization/modeling.py`, `imaging/features/pixelization/fit.py`) demonstrate the
+`autolens_workspace/scripts/imaging/features/pixelization/modeling.py`,
+`autolens_workspace/scripts/imaging/features/pixelization/fit.py`) demonstrate the
 noise-scaling API by applying a `mask_extra_galaxies` mask to the dataset. Output an empty (all-False,
 no-pixels-masked) mask so those tutorials can call `apply_noise_scaling(mask=...)` without crashing on a
 missing FITS file. The mask shape tracks `dataset.shape_native`, so `PYAUTO_SMALL_DATASETS=1` is honoured
diff --git a/scripts/simulator/no_lens_light__mass_sis.py b/scripts/simulator/no_lens_light__mass_sis.py
index 87b2cc0..fa0f519 100644
--- a/scripts/simulator/no_lens_light__mass_sis.py
+++ b/scripts/simulator/no_lens_light__mass_sis.py
@@ -26,7 +26,7 @@
 
 __Start Here Notebook__
 
-If any code in this script is unclear, refer to the `simulators/start_here.ipynb` notebook.
+If any code in this script is unclear, refer to the `autolens_workspace/*/imaging/simulator.ipynb` notebook.
 """
 
 from autolens import jax_wrapper  # Sets JAX environment before other imports
diff --git a/scripts/simulator/source_complex.py b/scripts/simulator/source_complex.py
index c66a782..2ac973a 100644
--- a/scripts/simulator/source_complex.py
+++ b/scripts/simulator/source_complex.py
@@ -30,7 +30,7 @@
 
 __Start Here Notebook__
 
-If any code in this script is unclear, refer to the `simulators/start_here.ipynb` notebook.
+If any code in this script is unclear, refer to the `autolens_workspace/*/imaging/simulator.ipynb` notebook.
 """
 
 from autolens import jax_wrapper  # Sets JAX environment before other imports
diff --git a/workspace_index.json b/workspace_index.json
index 3136ee0..91e127e 100644
--- a/workspace_index.json
+++ b/workspace_index.json
@@ -24,7 +24,7 @@
       "Units"
     ],
     "cross_refs": [
-      "/guides/over_sampling.ipynb"
+      "/guides/advanced/over_sampling.ipynb"
     ],
     "notebook": "notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb",
     "path": "scripts/chapter_1_introduction/tutorial_1_grids_and_galaxies.py",
@@ -149,7 +149,7 @@
       "Wrap Up"
     ],
     "cross_refs": [
-      "/imaging/log_likelihood_function/parametric.ipynb"
+      "/imaging/likelihood_function.ipynb"
     ],
     "notebook": "notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb",
     "path": "scripts/chapter_2_lens_modeling/tutorial_1_non_linear_search.py",
@@ -177,7 +177,7 @@
       "Wrap Up"
     ],
     "cross_refs": [
-      "scripts/howtogalaxy/chapter_2_modeling/tutorial_2_practicalities.py"
+      "scripts/chapter_2_lens_modeling/tutorial_2_practicalities.py"
     ],
     "notebook": "notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb",
     "path": "scripts/chapter_2_lens_modeling/tutorial_2_practicalities.py",
@@ -210,7 +210,7 @@
       "Discussion"
     ],
     "cross_refs": [
-      "howtolens/chapter_optional/tutorial_searches.ipynb"
+      "chapter_optional/tutorial_searches.ipynb"
     ],
     "notebook": "notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb",
     "path": "scripts/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.py",
@@ -236,8 +236,8 @@
       "Wrap Up"
     ],
     "cross_refs": [
-      "/modeling/features/multi_gaussian_expansion.py",
-      "autolens_workspace/scripts/modeling/features/shapelets.py"
+      "/imaging/features/multi_gaussian_expansion/modeling.py",
+      "autolens_workspace/scripts/imaging/features/advanced/shapelets/modeling.py"
     ],
     "notebook": "notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb",
     "path": "scripts/chapter_2_lens_modeling/tutorial_5_linear_profiles.py",
@@ -435,7 +435,7 @@
       "Detailed Explanation"
     ],
     "cross_refs": [
-      "/imaging/log_likelihood_function/inversion.ipynb"
+      "/imaging/features/pixelization/likelihood_function.ipynb"
     ],
     "notebook": "notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb",
     "path": "scripts/chapter_4_pixelizations/tutorial_3_inversions.py",
@@ -500,7 +500,7 @@
   {
     "contents": [],
     "cross_refs": [
-      "/imaging/features/pixelizations/modeling.py"
+      "/imaging/features/pixelization/modeling.py"
     ],
     "notebook": "notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb",
     "path": "scripts/chapter_4_pixelizations/tutorial_8_model_fit.py",
@@ -546,7 +546,7 @@
       "Tracer json"
     ],
     "cross_refs": [
-      "simulators/start_here.ipynb",
+      "/imaging/simulator.ipynb",
       "start_here.py"
     ],
     "notebook": "notebooks/simulator/lens_sersic.ipynb",
@@ -565,7 +565,7 @@
       "Tracer json"
     ],
     "cross_refs": [
-      "simulators/start_here.ipynb"
+      "/imaging/simulator.ipynb"
     ],
     "notebook": "notebooks/simulator/lens_x2.ipynb",
     "path": "scripts/simulator/lens_x2.py",
@@ -584,10 +584,10 @@
       "Tracer json"
     ],
     "cross_refs": [
-      "autolens_workspace/notebooks/modeling/features/no_lens_light.ipynb",
-      "imaging/features/pixelization/fit.py",
-      "imaging/features/pixelization/modeling.py",
-      "simulators/start_here.ipynb",
+      "/imaging/simulator.ipynb",
+      "autolens_workspace/notebooks/imaging/features/no_lens_light/modeling.ipynb",
+      "autolens_workspace/scripts/imaging/features/pixelization/fit.py",
+      "autolens_workspace/scripts/imaging/features/pixelization/modeling.py",
       "start_here.py"
     ],
     "notebook": "notebooks/simulator/no_lens_light.ipynb",
@@ -606,7 +606,7 @@
       "Tracer json"
     ],
     "cross_refs": [
-      "simulators/start_here.ipynb",
+      "/imaging/simulator.ipynb",
       "start_here.py"
     ],
     "notebook": "notebooks/simulator/no_lens_light__mass_sis.ipynb",
@@ -625,7 +625,7 @@
       "Tracer json"
     ],
     "cross_refs": [
-      "simulators/start_here.ipynb"
+      "/imaging/simulator.ipynb"
     ],
     "notebook": "notebooks/simulator/source_complex.ipynb",
     "path": "scripts/simulator/source_complex.py",