Added V2 and ISA support

.pylintdict

@@ -362,6 +362,7 @@ trainability
 transpilation
 transpile
 transpiled
+transpiler
 trotterization
 trotterized
 uncompute

qiskit_algorithms/amplitude_amplifiers/grover.py

@@ -18,16 +18,14 @@
 from typing import Any
 
 import numpy as np
-
 from qiskit import ClassicalRegister, QuantumCircuit
-from qiskit.primitives import BaseSampler
-from qiskit.quantum_info import Statevector
+from qiskit.primitives import BaseSamplerV2
 
 from qiskit_algorithms.exceptions import AlgorithmError
 from qiskit_algorithms.utils import algorithm_globals
-
 from .amplification_problem import AmplificationProblem
 from .amplitude_amplifier import AmplitudeAmplifier, AmplitudeAmplifierResult
+from ..custom_types import Transpiler
 
 
 class Grover(AmplitudeAmplifier):
@@ -116,7 +114,9 @@ def __init__(
         iterations: list[int] | Iterator[int] | int | None = None,
         growth_rate: float | None = None,
         sample_from_iterations: bool = False,
-        sampler: BaseSampler | None = None,
+        sampler: BaseSamplerV2 | None = None,
+        transpiler: Transpiler | None = None,
+        transpiler_options: dict[str, Any] | None = None,
     ) -> None:
         r"""
         Args:
@@ -136,6 +136,11 @@ def __init__(
                 powers of the Grover operator, a random integer sample between 0 and smaller value
                 than the iteration is used as a power, see [1], Section 4.
             sampler: A Sampler to use for sampling the results of the circuits.
+            transpiler: An optional object with a `run` method allowing to transpile the circuits
+                that are produced within this algorithm. If set to `None`, these won't be
+                transpiled.
+            transpiler_options: A dictionary of options to be passed to the transpiler's `run`
+                method as keyword arguments.
 
         Raises:
             ValueError: If ``growth_rate`` is a float but not larger than 1.
@@ -165,9 +170,11 @@ def __init__(
         self._sampler = sampler
         self._sample_from_iterations = sample_from_iterations
         self._iterations_arg = iterations
+        self._transpiler = transpiler
+        self._transpiler_options = transpiler_options if transpiler_options is not None else {}
 
     @property
-    def sampler(self) -> BaseSampler | None:
+    def sampler(self) -> BaseSamplerV2 | None:
         """Get the sampler.
 
         Returns:
@@ -176,7 +183,7 @@ def sampler(self) -> BaseSampler | None:
         return self._sampler
 
     @sampler.setter
-    def sampler(self, sampler: BaseSampler) -> None:
+    def sampler(self, sampler: BaseSamplerV2) -> None:
         """Set the sampler.
 
         Args:
@@ -234,23 +241,29 @@ def amplify(self, amplification_problem: AmplificationProblem) -> "GroverResult"
             # sample from [0, power) if specified
             if self._sample_from_iterations:
                 power = algorithm_globals.random.integers(power)
+
             # Run a grover experiment for a given power of the Grover operator.
-            if self._sampler is not None:
-                qc = self.construct_circuit(amplification_problem, power, measurement=True)
-                job = self._sampler.run([qc])
-
-                try:
-                    results = job.result()
-                except Exception as exc:
-                    raise AlgorithmError("Sampler job failed.") from exc
-
-                num_bits = len(amplification_problem.objective_qubits)
-                circuit_results: dict[str, Any] | Statevector | np.ndarray = {
-                    np.binary_repr(k, num_bits): v for k, v in results.quasi_dists[0].items()
-                }
-                top_measurement, max_probability = max(
-                    circuit_results.items(), key=lambda x: x[1]  # type: ignore[union-attr]
-                )
+            qc = self.construct_circuit(amplification_problem, power, measurement=True)
+
+            if self._transpiler is not None:
+                qc = self._transpiler.run(qc, **self._transpiler_options)
+
+            job = self._sampler.run([qc])
+
+            try:
+                results = job.result()
+            except Exception as exc:
+                raise AlgorithmError("Sampler job failed.") from exc
+
+            circuit_results = getattr(results[0].data, qc.cregs[0].name)
+            circuit_results = {
+                label: value / circuit_results.num_shots
+                for label, value in circuit_results.get_counts().items()
+            }
+
+            top_measurement, max_probability = max(
+                circuit_results.items(), key=lambda x: x[1]  # type: ignore[union-attr]
+            )
 
             all_circuit_results.append(circuit_results)
 

qiskit_algorithms/custom_types.py

@@ -0,0 +1,28 @@
+# This code is part of a Qiskit project.
+#
+# (C) Copyright IBM 2024.
+#
+# 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
+# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
+#
+# Any modifications or derivative works of this code must retain this
+# copyright notice, and modified files need to carry a notice indicating
+# that they have been altered from the originals.
+
+"""Types used by the qiskit-algorithms package."""
+from __future__ import annotations
+
+from typing import Any, Protocol, Union
+
+from qiskit import QuantumCircuit
+
+_Circuits = Union[list[QuantumCircuit], QuantumCircuit]
+
+
+class Transpiler(Protocol):
+    """A Generic type to represent a transpiler."""
+
+    def run(self, circuits: _Circuits, **options: Any) -> _Circuits:
+        """Transpile a circuit or a list of quantum circuits."""
+        pass

qiskit_algorithms/eigensolvers/vqd.py

@@ -25,7 +25,7 @@
 import numpy as np
 
 from qiskit.circuit import QuantumCircuit
-from qiskit.primitives import BaseEstimator
+from qiskit.primitives import BaseEstimatorV2
 from qiskit.quantum_info.operators.base_operator import BaseOperator
 from qiskit.quantum_info import SparsePauliOp
 
@@ -88,7 +88,7 @@ class VQD(VariationalAlgorithm, Eigensolver):
     updated once the VQD object has been constructed.
 
     Attributes:
-            estimator (BaseEstimator): The primitive instance used to perform the expectation
+            estimator (BaseEstimatorV2): The primitive instance used to perform the expectation
                 estimation as indicated in the VQD paper.
             fidelity (BaseStateFidelity): The fidelity class instance used to compute the
                 overlap estimation as indicated in the VQD paper.
@@ -112,7 +112,7 @@ class VQD(VariationalAlgorithm, Eigensolver):
 
     def __init__(
         self,
-        estimator: BaseEstimator,
+        estimator: BaseEstimatorV2,
         fidelity: BaseStateFidelity,
         ansatz: QuantumCircuit,
         optimizer: Optimizer | Minimizer | Sequence[Optimizer | Minimizer],
@@ -389,9 +389,7 @@ def evaluate_energy(parameters: np.ndarray) -> float | np.ndarray:
                 parameters = np.reshape(parameters, (-1, num_parameters))
             batch_size = len(parameters)
 
-            estimator_job = self.estimator.run(
-                batch_size * [self.ansatz], batch_size * [operator], parameters
-            )
+            estimator_job = self.estimator.run([(self.ansatz, operator, parameters)])
 
             total_cost = np.zeros(batch_size)
 
@@ -410,18 +408,17 @@ def evaluate_energy(parameters: np.ndarray) -> float | np.ndarray:
                     total_cost += np.real(betas[state] * cost)
 
             try:
-                estimator_result = estimator_job.result()
+                estimator_result = estimator_job.result()[0]
 
             except Exception as exc:
                 raise AlgorithmError("The primitive job to evaluate the energy failed!") from exc
 
-            values = estimator_result.values + total_cost
+            values = estimator_result.data.evs + total_cost
 
             if self.callback is not None:
-                metadata = estimator_result.metadata
-                for params, value, meta in zip(parameters, values, metadata):
+                for params, value in zip(parameters, values):
                     self._eval_count += 1
-                    self.callback(self._eval_count, params, value, meta, step)
+                    self.callback(self._eval_count, params, value, estimator_result.metadata, step)
             else:
                 self._eval_count += len(values)
 

qiskit_algorithms/observables_evaluator.py

@@ -20,15 +20,15 @@
 
 from qiskit import QuantumCircuit
 from qiskit.quantum_info import SparsePauliOp
-from qiskit.primitives import BaseEstimator
+from qiskit.primitives import BaseEstimatorV2
 from qiskit.quantum_info.operators.base_operator import BaseOperator
 
 from .exceptions import AlgorithmError
 from .list_or_dict import ListOrDict
 
 
 def estimate_observables(
-    estimator: BaseEstimator,
+    estimator: BaseEstimatorV2,
     quantum_state: QuantumCircuit,
     observables: ListOrDict[BaseOperator],
     parameter_values: Sequence[float] | None = None,
@@ -63,21 +63,19 @@ def estimate_observables(
 
     if len(observables_list) > 0:
         observables_list = _handle_zero_ops(observables_list)
-        quantum_state = [quantum_state] * len(observables)
         parameter_values_: Sequence[float] | Sequence[Sequence[float]] | None = parameter_values
-        if parameter_values is not None:
-            parameter_values_ = [parameter_values] * len(observables)
         try:
-            estimator_job = estimator.run(quantum_state, observables_list, parameter_values_)
-            expectation_values = estimator_job.result().values
+            estimator_job = estimator.run([(quantum_state, observables_list, parameter_values_)])
+            estimator_result = estimator_job.result()[0]
+            expectation_values = estimator_result.data.evs
         except Exception as exc:
             raise AlgorithmError("The primitive job failed!") from exc
 
-        metadata = estimator_job.result().metadata
+        metadata = estimator_result.metadata
         # Discard values below threshold
         observables_means = expectation_values * (np.abs(expectation_values) > threshold)
         # zip means and metadata into tuples
-        observables_results = list(zip(observables_means, metadata))
+        observables_results = list(zip(observables_means, [metadata] * len(observables_means)))
     else:
         observables_results = []
 

qiskit_algorithms/phase_estimators/hamiltonian_phase_estimation.py

@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2020, 2023.
+# (C) Copyright IBM 2020, 2024.
 #
 # 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
@@ -14,16 +14,16 @@
 
 from __future__ import annotations
 
-
 from qiskit import QuantumCircuit
 from qiskit.circuit.library import PauliEvolutionGate
-from qiskit.primitives import BaseSampler
+from qiskit.primitives import BaseSamplerV2
 from qiskit.quantum_info import SparsePauliOp, Statevector, Pauli
 from qiskit.synthesis import EvolutionSynthesis
 
-from .phase_estimation import PhaseEstimation
 from .hamiltonian_phase_estimation_result import HamiltonianPhaseEstimationResult
+from .phase_estimation import PhaseEstimation
 from .phase_estimation_scale import PhaseEstimationScale
+from ..custom_types import Transpiler
 
 
 class HamiltonianPhaseEstimation:
@@ -83,17 +83,22 @@ class HamiltonianPhaseEstimation:
     def __init__(
         self,
         num_evaluation_qubits: int,
-        sampler: BaseSampler | None = None,
+        sampler: BaseSamplerV2 | None = None,
+        transpiler: Transpiler | None = None,
     ) -> None:
         r"""
         Args:
             num_evaluation_qubits: The number of qubits used in estimating the phase. The phase will
                 be estimated as a binary string with this many bits.
             sampler: The sampler primitive on which the circuit will be sampled.
+            transpiler: An optional object with a `run` method allowing to transpile the circuits
+                that are produced within this algorithm. If set to `None`, these won't be
+                transpiled.
         """
         self._phase_estimation = PhaseEstimation(
             num_evaluation_qubits=num_evaluation_qubits,
             sampler=sampler,
+            transpiler=transpiler,
         )
 
     def _get_scale(self, hamiltonian, bound=None) -> PhaseEstimationScale:

qiskit_algorithms/phase_estimators/ipe.py

@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2021, 2023.
+# (C) Copyright IBM 2021, 2024.
 #
 # 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
@@ -19,12 +19,13 @@
 
 from qiskit.circuit import QuantumCircuit, QuantumRegister
 from qiskit.circuit.classicalregister import ClassicalRegister
-from qiskit.primitives import BaseSampler
+from qiskit.primitives import BaseSamplerV2
 
 from qiskit_algorithms.exceptions import AlgorithmError
 
 from .phase_estimator import PhaseEstimator
 from .phase_estimator import PhaseEstimatorResult
+from ..custom_types import Transpiler
 
 
 class IterativePhaseEstimation(PhaseEstimator):
@@ -40,12 +41,16 @@ class IterativePhaseEstimation(PhaseEstimator):
     def __init__(
         self,
         num_iterations: int,
-        sampler: BaseSampler | None = None,
+        sampler: BaseSamplerV2 | None = None,
+        transpiler: Transpiler | None = None,
     ) -> None:
         r"""
         Args:
             num_iterations: The number of iterations (rounds) of the phase estimation to run.
             sampler: The sampler primitive on which the circuit will be sampled.
+            transpiler: An optional object with a `run` method allowing to transpile the circuits
+                that are produced within this algorithm. If set to `None`, these won't be
+                transpiled.
 
         Raises:
             ValueError: if num_iterations is not greater than zero.
@@ -58,6 +63,7 @@ def __init__(
             raise ValueError("`num_iterations` must be greater than zero.")
         self._num_iterations = num_iterations
         self._sampler = sampler
+        self._pass_manager = transpiler
 
     def construct_circuit(
         self,
@@ -125,9 +131,17 @@ def _estimate_phase_iteratively(self, unitary, state_preparation):
             qc = self.construct_circuit(
                 unitary, state_preparation, k, -2 * numpy.pi * omega_coef, True
             )
+
+            if self._pass_manager is not None:
+                qc = self._pass_manager.run(qc)
+
             try:
                 sampler_job = self._sampler.run([qc])
-                result = sampler_job.result().quasi_dists[0]
+                result = sampler_job.result()[0].data.c
+                result = {
+                    label: value / result.num_shots
+                    for label, value in result.get_int_counts().items()
+                }
             except Exception as exc:
                 raise AlgorithmError("The primitive job failed!") from exc
             x = 1 if result.get(1, 0) > result.get(0, 0) else 0