add reno

qiskit_optimization/__init__.py

@@ -29,7 +29,8 @@
 (:class:`~qiskit.algorithms.minimum_eigensolver.QAOA`), to
 `Grover Adaptive Search <https://arxiv.org/abs/quant-ph/9607014>`_
 (:class:`~algorithms.GroverOptimizer`), leveraging
-fundamental :mod:`~qiskit.algorithms.minimum_eigensolver` provided by Qiskit Terra. Furthermore, the modular design
+fundamental :mod:`~qiskit.algorithms.minimum_eigensolver` provided by Qiskit Terra.
+Furthermore, the modular design
 of the optimization module allows it to be easily extended and facilitates rapid development and
 testing of new algorithms. Compatible classical optimizers are also provided for testing,
 validation, and benchmarking.

qiskit_optimization/algorithms/warm_start_qaoa_optimizer.py

@@ -18,6 +18,7 @@
 
 import numpy as np
 from qiskit import QuantumCircuit
+from qiskit.algorithms import QAOA as LegacyQAOA
 from qiskit.algorithms.minimum_eigensolvers import QAOA
 from qiskit.circuit import Parameter
 
@@ -202,7 +203,7 @@ def __init__(
         self,
         pre_solver: OptimizationAlgorithm,
         relax_for_pre_solver: bool,
-        qaoa: QAOA,
+        qaoa: Union[QAOA, LegacyQAOA],
         epsilon: float = 0.25,
         num_initial_solutions: int = 1,
         warm_start_factory: Optional[WarmStartQAOAFactory] = None,

qiskit_optimization/deprecation.py

@@ -1,6 +1,6 @@
 # This code is part of Qiskit.
 #
-# (C) Copyright IBM 2021.
+# (C) Copyright IBM 2021, 2022.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory

releasenotes/notes/add-primitives-support-31af39549b5e66e3.yaml

@@ -0,0 +1,24 @@
+---
+features:
+  - |
+    The :class:`~.GroverOptimizer` class has a new keyword argument, ``sampler`` which is
+    used to run the algorithm using an instance of the :class:`~.BaseSampler`
+    interface to calculate the results. This new argument supersedes
+    the ``quantum_instance`` argument and accordingly, ``quantum_instance``
+    is pending deprecation and will be deprecated and subsequently removed in
+    future releases.
+  - |
+    The :class:`~.MinimumEigenOptimizer` class takes the primitives-based algorithms
+    (``qiskit.algorithms.minimum_eigensolvers.SamplingVQE`` and
+    ``qiskit.algorithms.minimum_eigensolvers.NumPyMinimumEigensolver``)
+    as ``min_eigen_solver`` argument.
+    The conventional algorithms ``qiskit.algorithms.minimum_eigen_solvers.MinimumEigensolver``
+    is pending deprecation and will be deprecated and subsequently removed in future releases.
+    Note that ``qiskit.algorithms.minimum_eigensolvers.SamplingVQE`` supersedes
+    ``qiskit.algorithms.VQE`` for :class:`~.MinimumEigenOptimizer`.
+  - |
+    The :class:`~.WarmStartQAOAOptimizer` class takes the primitives-based QAOA
+    (``qiskit.algorithms.minimum_eigensolvers.QAOA``) as ``qaoa`` argument.
+    The conventional algorithm ``qiskit.algorithms.minimum_eigen_solvers.QAOA``
+    is pending deprecation and will be deprecated
+    and subsequently removed in future releases.

test/algorithms/legacy/test_min_eigen_optimizer.py

@@ -43,7 +43,6 @@
 )
 from qiskit_optimization.problems import QuadraticProgram
 from qiskit_optimization.runtime import VQEProgram, QAOAProgram
-from qiskit_optimization.deprecation import clear_deprecated_objects
 
 
 @ddt

test/algorithms/legacy/test_warm_start_qaoa.py

@@ -10,7 +10,7 @@
 # copyright notice, and modified files need to carry a notice indicating
 # that they have been altered from the originals.
 
-""" Test warm start QAOA optimizer with legacy MinimumEigensolver. """
+""" Test warm start QAOA optimizer with legacy QAOA. """
 
 import unittest
 from test import QiskitOptimizationTestCase