docs: Add v0.7.3 release notes (#2301)

* Forward port PR #2290 and #2294 from `release/v0.7.x` to `main`.
* Add release notes for pyhf v0.7.3.

docs/release-notes.rst

@@ -2,6 +2,7 @@
 Release Notes
 =============
 
+.. include:: release-notes/v0.7.3.rst
 .. include:: release-notes/v0.7.2.rst
 .. include:: release-notes/v0.7.1.rst
 .. include:: release-notes/v0.7.0.rst

docs/release-notes/v0.7.3.rst

@@ -0,0 +1,78 @@
+|release v0.7.3|_
+=================
+
+This is a patch release from ``v0.7.2`` → ``v0.7.3``.
+
+Fixes
+-----
+
+* Use :func:`numpy.prod` API over ``numpy.product`` as ``numpy.product`` is
+  |np.product deprecation|_.
+  (PR :pr:`2242`)
+* Guard :class:`pyhf.optimize.opt_minuit.minuit_optimizer` optimizer strategy
+  from :obj:`None` to ensure :attr:`iminuit.Minuit.strategy` strategies
+  are correctly handled.
+  (PRs :pr:`2277`, :pr:`2278`)
+
+  The fixed bug was subtle and only occurred for specific configurations of
+  settings and arguments where ``do_grad=False`` was used (either explicitly
+  by provided kwarg or implicitly through defaults).
+  To determine if you might have been affected by it, check your code for
+  setups like the following.
+
+  .. code:: python
+
+    # Bug is backend independent. JAX is selected as an example where
+    # do_grad=False might be selected in response to the backend's value of
+    # pyhf.tensorlib.default_do_grad being True.
+    pyhf.set_backend("jax", pyhf.optimize.minuit_optimizer(strategy=0))
+
+    ...
+
+    fit_result, opt_result = pyhf.infer.mle.fit(
+        data, model, return_result_obj=True, do_grad=False
+    )
+    assert opt_result.minuit.strategy.strategy == 0  # fails for pyhf v0.7.2
+
+  Full example that fails in ``pyhf`` ``v0.7.2``:
+
+  .. code:: python
+
+    import pyhf
+
+    pyhf.set_backend("jax", pyhf.optimize.minuit_optimizer(strategy=0))
+
+    model = pyhf.simplemodels.uncorrelated_background(
+        signal=[12.0, 11.0], bkg=[50.0, 52.0], bkg_uncertainty=[3.0, 7.0]
+    )
+    data = [51, 48] + model.config.auxdata
+
+    # passing with strategy kwarg explicitly given
+    fit_result, opt_result = pyhf.infer.mle.fit(
+        data, model, return_result_obj=True, do_grad=False, strategy=0
+    )
+    minuit_strategy = opt_result.minuit.strategy.strategy
+    print(f"# Minuit minimization strategy: {minuit_strategy}")
+    assert minuit_strategy == 0
+
+    # strategy kwarg not given
+    fit_result, opt_result = pyhf.infer.mle.fit(
+        data, model, return_result_obj=True, do_grad=False
+    )
+    minuit_strategy = opt_result.minuit.strategy.strategy
+    print(f"# Minuit minimization strategy: {minuit_strategy}")
+    assert minuit_strategy == 0  # fails for pyhf v0.7.2
+
+Contributors
+------------
+
+``v0.7.3`` benefited from contributions from:
+
+* Alexander Held
+* Daniel Werner
+
+.. |release v0.7.3| replace:: ``v0.7.3``
+.. _`release v0.7.3`: https://github.com/scikit-hep/pyhf/releases/tag/v0.7.3
+
+.. |np.product deprecation| replace:: deprecated as of NumPy ``v1.25.0``
+.. _`np.product deprecation`: https://numpy.org/devdocs/release/1.25.0-notes.html#deprecations