docs(searches): add multi-start gradient searches to the modeling searches guide#133
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…rches guide Add a MultiStartAdam section to scripts/guides/modeling/searches.py documenting af.MultiStartAdam (with MultiStartADABelief / MultiStartLion as alternatives) — the JAX multi-start gradient MAP optimizer that works on the complex model parameter spaces where single-start LBFGS gets stuck. Config-only, mirroring the LBFGS section; regenerate the paired notebook. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Summary
Phase 3 of the multi-start gradient MAP search promotion (PyAutoFit#1369). Adds a MultiStartAdam section to
scripts/guides/modeling/searches.pydocumentingaf.MultiStartAdam(withMultiStartADABelief/MultiStartLionnoted as drop-in optax-rule alternatives), positioned after LBFGS. Framed against the caveat the guide already states — that optimizers struggle on complex model parameter spaces — since multi-start Adam is the optimizer that works there (its wide population of parallel starts escapes the local maxima that trap single-start LBFGS).This guide is a configuration reference (it constructs search objects to document the API/settings; it does not run fits), so the addition mirrors how LBFGS is shown — a config block + prose. Contents updated; paired notebook regenerated.
Test Plan
searches.pyparses;af.MultiStartAdam(path_prefix=..., name="MultiStartAdam", n_starts=50, n_steps=500, learning_rate=0.01)constructspy_to_notebook+ colab-injection transform; diff scoped tosearches.py+searches.ipynbResolves #132.
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