docs: api/modeling.rst points at PyAutoFit's search capability matrix (search-extensibility A1)

docs/api/modeling.rst

@@ -23,24 +23,13 @@ It acts as an interface between the data, model and the non-linear search.
 Non-linear Searches
 -------------------
 
-A non-linear search is an algorithm which fits a model to data.
-
-**PyAutoGalaxy** currently supports three types of non-linear search algorithms: nested samplers,
-Markov Chain Monte Carlo (MCMC) and Maximum Likelihood Estimaotrs (MLE).
+A non-linear search is an algorithm which fits a model to data. The searches are provided by
+**PyAutoFit**, and every one can be used with **PyAutoGalaxy**: see PyAutoFit's
+:ref:`capability matrix <autofit:search_capability_matrix>`, which lists every search, what it
+supports (JAX, gradients, evidence, posterior kind, install) and links to its API reference.
 
 .. currentmodule:: autofit
 
-.. autosummary::
-   :toctree: _autosummary
-   :template: custom-class-template.rst
-   :recursive:
-
-   Nautilus
-   LBFGS
-   BFGS
-   DynestyDynamic
-   Emcee
-
 Priors
 ------
 

docs/conf.py

@@ -65,6 +65,9 @@
 
 intersphinx_mapping = {
     "python": ("https://docs.python.org/3", None),
+    # PyAutoFit owns the non-linear searches; api/modeling.rst links to its
+    # generated capability matrix (search_capability_matrix).
+    "autofit": ("https://pyautofit.readthedocs.io/en/latest", None),
     "sphinx": ("https://www.sphinx-doc.org/en/master", None),
 }