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Bump pypa/cibuildwheel from 2.19.1 to 2.19.2 in the github_actions group (#12733) (#12737)

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Updates `pypa/cibuildwheel` from 2.19.1 to 2.19.2
- [Release notes](https://github.com/pypa/cibuildwheel/releases)
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- dependency-name: pypa/cibuildwheel
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  update-type: version-update:semver-patch
  dependency-group: github_actions
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88.2

/qiskit/transpiler/passes/synthesis/unitary_synthesis.py

# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2020.
#
# 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.

"""
=========================================================================================
Unitary Synthesis Plugin (in :mod:`qiskit.transpiler.passes.synthesis.unitary_synthesis`)
=========================================================================================

.. autosummary::
   :toctree: ../stubs/

   DefaultUnitarySynthesis
"""

from __future__ import annotations
from math import pi, inf, isclose
from typing import Any
from itertools import product
from functools import partial
import numpy as np

from qiskit.converters import circuit_to_dag, dag_to_circuit
from qiskit.transpiler import CouplingMap, Target
from qiskit.transpiler.basepasses import TransformationPass
from qiskit.transpiler.exceptions import TranspilerError
from qiskit.dagcircuit.dagcircuit import DAGCircuit
from qiskit.synthesis.one_qubit import one_qubit_decompose
from qiskit.transpiler.passes.optimization.optimize_1q_decomposition import _possible_decomposers
from qiskit.synthesis.two_qubit.xx_decompose import XXDecomposer, XXEmbodiments
from qiskit.synthesis.two_qubit.two_qubit_decompose import (
    TwoQubitBasisDecomposer,
    TwoQubitWeylDecomposition,
    GATE_NAME_MAP,
)
from qiskit.quantum_info import Operator
from qiskit.circuit import ControlFlowOp, Gate, Parameter
from qiskit.circuit.library.standard_gates import (
    iSwapGate,
    CXGate,
    CZGate,
    RXXGate,
    RZXGate,
    ECRGate,
)
from qiskit.transpiler.passes.synthesis import plugin
from qiskit.transpiler.passes.optimization.optimize_1q_decomposition import (
    Optimize1qGatesDecomposition,
)
from qiskit.providers.models import BackendProperties
from qiskit.circuit.library.standard_gates import get_standard_gate_name_mapping
from qiskit.exceptions import QiskitError


KAK_GATE_NAMES = {
    "cx": CXGate(),
    "cz": CZGate(),
    "iswap": iSwapGate(),
    "rxx": RXXGate(pi / 2),
    "ecr": ECRGate(),
    "rzx": RZXGate(pi / 4),  # typically pi/6 is also available
}

GateNameToGate = get_standard_gate_name_mapping()


def _choose_kak_gate(basis_gates):
    """Choose the first available 2q gate to use in the KAK decomposition."""
    kak_gate = None
    kak_gates = set(basis_gates or []).intersection(KAK_GATE_NAMES.keys())
    if kak_gates:
        kak_gate = KAK_GATE_NAMES[kak_gates.pop()]

    return kak_gate


def _choose_euler_basis(basis_gates):
    """Choose the first available 1q basis to use in the Euler decomposition."""
    basis_set = set(basis_gates or [])
    decomposers = _possible_decomposers(basis_set)
    if decomposers:
        return decomposers[0]
    return "U"


def _find_matching_euler_bases(target, qubit):
    """Find matching available 1q basis to use in the Euler decomposition."""
    basis_set = target.operation_names_for_qargs((qubit,))
    return _possible_decomposers(basis_set)


def _choose_bases(basis_gates, basis_dict=None):
    """Find the matching basis string keys from the list of basis gates from the backend."""
    if basis_gates is None:
        basis_set = set()
    else:
        basis_set = set(basis_gates)

    if basis_dict is None:
        basis_dict = one_qubit_decompose.ONE_QUBIT_EULER_BASIS_GATES

    out_basis = []
    for basis, gates in basis_dict.items():
        if set(gates).issubset(basis_set):
            out_basis.append(basis)

    return out_basis


def _decomposer_2q_from_basis_gates(basis_gates, pulse_optimize=None, approximation_degree=None):
    decomposer2q = None
    kak_gate = _choose_kak_gate(basis_gates)
    euler_basis = _choose_euler_basis(basis_gates)
    basis_fidelity = approximation_degree or 1.0
    if isinstance(kak_gate, RZXGate):
        backup_optimizer = TwoQubitBasisDecomposer(
            CXGate(),
            basis_fidelity=basis_fidelity,
            euler_basis=euler_basis,
            pulse_optimize=pulse_optimize,
        )
        decomposer2q = XXDecomposer(euler_basis=euler_basis, backup_optimizer=backup_optimizer)
    elif kak_gate is not None:
        decomposer2q = TwoQubitBasisDecomposer(
            kak_gate,
            basis_fidelity=basis_fidelity,
            euler_basis=euler_basis,
            pulse_optimize=pulse_optimize,
        )
    return decomposer2q


def _error(circuit, target=None, qubits=None):
    """
    Calculate a rough error for a `circuit` that runs on specific
    `qubits` of `target`.

    Use basis errors from target if available, otherwise use length
    of circuit as a weak proxy for error.
    """
    if target is None:
        if isinstance(circuit, DAGCircuit):
            return len(circuit.op_nodes())
        else:
            return len(circuit)
    gate_fidelities = []
    gate_durations = []

    def score_instruction(inst, inst_qubits):
        try:
            keys = target.operation_names_for_qargs(inst_qubits)
            for key in keys:
                target_op = target.operation_from_name(key)
                if isinstance(circuit, DAGCircuit):
                    op = inst.op
                else:
                    op = inst.operation
                if isinstance(target_op, op.base_class) and (
                    target_op.is_parameterized()
                    or all(
                        isclose(float(p1), float(p2)) for p1, p2 in zip(target_op.params, op.params)
                    )
                ):
                    inst_props = target[key].get(inst_qubits, None)
                    if inst_props is not None:
                        error = getattr(inst_props, "error", 0.0) or 0.0
                        duration = getattr(inst_props, "duration", 0.0) or 0.0
                        gate_fidelities.append(1 - error)
                        gate_durations.append(duration)
                    else:
                        gate_fidelities.append(1.0)
                        gate_durations.append(0.0)

                    break
            else:
                raise KeyError
        except KeyError as error:
            if isinstance(circuit, DAGCircuit):
                op = inst.op
            else:
                op = inst.operation
            raise TranspilerError(
                f"Encountered a bad synthesis. " f"Target has no {op} on qubits {qubits}."
            ) from error

    if isinstance(circuit, DAGCircuit):
        for inst in circuit.topological_op_nodes():
            inst_qubits = tuple(qubits[circuit.find_bit(q).index] for q in inst.qargs)
            score_instruction(inst, inst_qubits)
    else:
        for inst in circuit:
            inst_qubits = tuple(qubits[circuit.find_bit(q).index] for q in inst.qubits)
            score_instruction(inst, inst_qubits)
    # TODO:return np.sum(gate_durations)
    return 1 - np.prod(gate_fidelities)


def _preferred_direction(
    decomposer2q, qubits, natural_direction, coupling_map=None, gate_lengths=None, gate_errors=None
):
    """
    `decomposer2q` decomposes an SU(4) over `qubits`. A user sets `natural_direction`
    to indicate whether they prefer synthesis in a hardware-native direction.
    If yes, we return the `preferred_direction` here. If no hardware direction is
    preferred, we raise an error (unless natural_direction is None).
    We infer this from `coupling_map`, `gate_lengths`, `gate_errors`.

    Returns [0, 1] if qubits are correct in the hardware-native direction.
    Returns [1, 0] if qubits must be flipped to match hardware-native direction.
    """
    qubits_tuple = tuple(qubits)
    reverse_tuple = qubits_tuple[::-1]

    preferred_direction = None
    if natural_direction in {None, True}:
        # find native gate directions from a (non-bidirectional) coupling map
        if coupling_map is not None:
            neighbors0 = coupling_map.neighbors(qubits[0])
            zero_one = qubits[1] in neighbors0
            neighbors1 = coupling_map.neighbors(qubits[1])
            one_zero = qubits[0] in neighbors1
            if zero_one and not one_zero:
                preferred_direction = [0, 1]
            if one_zero and not zero_one:
                preferred_direction = [1, 0]
        # otherwise infer natural directions from gate durations or gate errors
        if preferred_direction is None and (gate_lengths or gate_errors):
            cost_0_1 = inf
            cost_1_0 = inf
            try:
                cost_0_1 = next(
                    duration
                    for gate, duration in gate_lengths.get(qubits_tuple, [])
                    if gate == decomposer2q.gate
                )
            except StopIteration:
                pass
            try:
                cost_1_0 = next(
                    duration
                    for gate, duration in gate_lengths.get(reverse_tuple, [])
                    if gate == decomposer2q.gate
                )
            except StopIteration:
                pass
            if not (cost_0_1 < inf or cost_1_0 < inf):
                try:
                    cost_0_1 = next(
                        error
                        for gate, error in gate_errors.get(qubits_tuple, [])
                        if gate == decomposer2q.gate
                    )
                except StopIteration:
                    pass
                try:
                    cost_1_0 = next(
                        error
                        for gate, error in gate_errors.get(reverse_tuple, [])
                        if gate == decomposer2q.gate
                    )
                except StopIteration:
                    pass
            if cost_0_1 < cost_1_0:
                preferred_direction = [0, 1]
            elif cost_1_0 < cost_0_1:
                preferred_direction = [1, 0]
    if natural_direction is True and preferred_direction is None:
        raise TranspilerError(
            f"No preferred direction of gate on qubits {qubits} "
            "could be determined from coupling map or "
            "gate lengths / gate errors."
        )
    return preferred_direction


class UnitarySynthesis(TransformationPass):
    """Synthesize gates according to their basis gates."""

    def __init__(
        self,
        basis_gates: list[str] = None,
        approximation_degree: float | None = 1.0,
        coupling_map: CouplingMap = None,
        backend_props: BackendProperties = None,
        pulse_optimize: bool | None = None,
        natural_direction: bool | None = None,
        synth_gates: list[str] | None = None,
        method: str = "default",
        min_qubits: int = 0,
        plugin_config: dict = None,
        target: Target = None,
    ):
        """Synthesize unitaries over some basis gates.

        This pass can approximate 2-qubit unitaries given some
        gate fidelities (either via ``backend_props`` or ``target``).
        More approximation can be forced by setting a heuristic dial
        ``approximation_degree``.

        Args:
            basis_gates (list[str]): List of gate names to target. If this is
                not specified the ``target`` argument must be used. If both this
                and the ``target`` are specified the value of ``target`` will
                be used and this will be ignored.
            approximation_degree (float): heuristic dial used for circuit approximation
                (1.0=no approximation, 0.0=maximal approximation). Approximation can
                make the synthesized circuit cheaper at the cost of straying from
                the original unitary. If None, approximation is done based on gate fidelities.
            coupling_map (CouplingMap): the coupling map of the backend
                in case synthesis is done on a physical circuit. The
                directionality of the coupling_map will be taken into
                account if ``pulse_optimize`` is ``True``/``None`` and ``natural_direction``
                is ``True``/``None``.
            backend_props (BackendProperties): Properties of a backend to
                synthesize for (e.g. gate fidelities).
            pulse_optimize (bool): Whether to optimize pulses during
                synthesis. A value of ``None`` will attempt it but fall
                back if it does not succeed. A value of ``True`` will raise
                an error if pulse-optimized synthesis does not succeed.
            natural_direction (bool): Whether to apply synthesis considering
                directionality of 2-qubit gates. Only applies when
                ``pulse_optimize`` is ``True`` or ``None``. The natural direction is
                determined by first checking to see whether the
                coupling map is unidirectional.  If there is no
                coupling map or the coupling map is bidirectional,
                the gate direction with the shorter
                duration from the backend properties will be used. If
                set to True, and a natural direction can not be
                determined, raises :class:`.TranspilerError`. If set to None, no
                exception will be raised if a natural direction can
                not be determined.
            synth_gates (list[str]): List of gates to synthesize. If None and
                ``pulse_optimize`` is False or None, default to
                ``['unitary']``. If ``None`` and ``pulse_optimize == True``,
                default to ``['unitary', 'swap']``
            method (str): The unitary synthesis method plugin to use.
            min_qubits: The minimum number of qubits in the unitary to synthesize. If this is set
                and the unitary is less than the specified number of qubits it will not be
                synthesized.
            plugin_config: Optional extra configuration arguments (as a ``dict``)
                which are passed directly to the specified unitary synthesis
                plugin. By default, this will have no effect as the default
                plugin has no extra arguments. Refer to the documentation of
                your unitary synthesis plugin on how to use this.
            target: The optional :class:`~.Target` for the target device the pass
                is compiling for. If specified this will supersede the values
                set for ``basis_gates``, ``coupling_map``, and ``backend_props``.

        Raises:
            TranspilerError: if ``method`` was specified but is not found in the
                installed plugins list. The list of installed plugins can be queried with
                :func:`~qiskit.transpiler.passes.synthesis.plugin.unitary_synthesis_plugin_names`
        """
        super().__init__()
        self._basis_gates = set(basis_gates or ())
        self._approximation_degree = approximation_degree
        self._min_qubits = min_qubits
        self.method = method
        self.plugins = None
        if method != "default":
            self.plugins = plugin.UnitarySynthesisPluginManager()
        self._coupling_map = coupling_map
        self._backend_props = backend_props
        self._pulse_optimize = pulse_optimize
        self._natural_direction = natural_direction
        self._plugin_config = plugin_config
        self._target = target
        if target is not None:
            self._coupling_map = self._target.build_coupling_map()
        if synth_gates:
            self._synth_gates = synth_gates
        else:
            if pulse_optimize:
                self._synth_gates = ["unitary", "swap"]
            else:
                self._synth_gates = ["unitary"]

        self._synth_gates = set(self._synth_gates) - self._basis_gates

        if self.method != "default" and self.method not in self.plugins.ext_plugins:
            raise TranspilerError(f"Specified method '{self.method}' not found in plugin list")

    def run(self, dag: DAGCircuit) -> DAGCircuit:
        """Run the UnitarySynthesis pass on ``dag``.

        Args:
            dag: input dag.

        Returns:
            Output dag with UnitaryGates synthesized to target basis.
        """

        # If there aren't any gates to synthesize in the circuit we can skip all the iteration
        # and just return.
        if not set(self._synth_gates).intersection(dag.count_ops()):
            return dag

        if self.plugins:
            plugin_method = self.plugins.ext_plugins[self.method].obj
        else:
            plugin_method = DefaultUnitarySynthesis()
        plugin_kwargs: dict[str, Any] = {"config": self._plugin_config}
        _gate_lengths = _gate_errors = None
        _gate_lengths_by_qubit = _gate_errors_by_qubit = None

        if self.method == "default":
            # If the method is the default, we only need to evaluate one set of keyword arguments.
            # To simplify later logic, and avoid cases where static analysis might complain that we
            # haven't initialised the "default" handler, we rebind the names so they point to the
            # same object as the chosen method.
            default_method = plugin_method
            default_kwargs = plugin_kwargs
            method_list = [(plugin_method, plugin_kwargs)]
        else:
            # If the method is not the default, we still need to initialise the default plugin's
            # keyword arguments in case we have to fall back on it during the actual run.
            default_method = self.plugins.ext_plugins["default"].obj
            default_kwargs = {}
            method_list = [(plugin_method, plugin_kwargs), (default_method, default_kwargs)]

        for method, kwargs in method_list:
            if method.supports_basis_gates:
                kwargs["basis_gates"] = self._basis_gates
            if method.supports_natural_direction:
                kwargs["natural_direction"] = self._natural_direction
            if method.supports_pulse_optimize:
                kwargs["pulse_optimize"] = self._pulse_optimize
            if method.supports_gate_lengths:
                _gate_lengths = _gate_lengths or _build_gate_lengths(
                    self._backend_props, self._target
                )
                kwargs["gate_lengths"] = _gate_lengths
            if method.supports_gate_errors:
                _gate_errors = _gate_errors or _build_gate_errors(self._backend_props, self._target)
                kwargs["gate_errors"] = _gate_errors
            if method.supports_gate_lengths_by_qubit:
                _gate_lengths_by_qubit = _gate_lengths_by_qubit or _build_gate_lengths_by_qubit(
                    self._backend_props, self._target
                )
                kwargs["gate_lengths_by_qubit"] = _gate_lengths_by_qubit
            if method.supports_gate_errors_by_qubit:
                _gate_errors_by_qubit = _gate_errors_by_qubit or _build_gate_errors_by_qubit(
                    self._backend_props, self._target
                )
                kwargs["gate_errors_by_qubit"] = _gate_errors_by_qubit
            supported_bases = method.supported_bases
            if supported_bases is not None:
                kwargs["matched_basis"] = _choose_bases(self._basis_gates, supported_bases)
            if method.supports_target:
                kwargs["target"] = self._target

        # Handle approximation degree as a special case for backwards compatibility, it's
        # not part of the plugin interface and only something needed for the default
        # pass.
        # pylint: disable=attribute-defined-outside-init
        default_method._approximation_degree = self._approximation_degree
        if self.method == "default":
            # pylint: disable=attribute-defined-outside-init
            plugin_method._approximation_degree = self._approximation_degree

        qubit_indices = (
            {bit: i for i, bit in enumerate(dag.qubits)}
            if plugin_method.supports_coupling_map or default_method.supports_coupling_map
            else {}
        )
        return self._run_main_loop(
            dag, qubit_indices, plugin_method, plugin_kwargs, default_method, default_kwargs
        )

    def _run_main_loop(
        self, dag, qubit_indices, plugin_method, plugin_kwargs, default_method, default_kwargs
    ):
        """Inner loop for the optimizer, after all DAG-independent set-up has been completed."""
        for node in dag.op_nodes(ControlFlowOp):
            node.op = node.op.replace_blocks(
                [
                    dag_to_circuit(
                        self._run_main_loop(
                            circuit_to_dag(block),
                            {
                                inner: qubit_indices[outer]
                                for inner, outer in zip(block.qubits, node.qargs)
                            },
                            plugin_method,
                            plugin_kwargs,
                            default_method,
                            default_kwargs,
                        ),
                        copy_operations=False,
                    )
                    for block in node.op.blocks
                ]
            )

        out_dag = dag.copy_empty_like()
        for node in dag.topological_op_nodes():
            if node.op.name == "unitary" and len(node.qargs) >= self._min_qubits:
                synth_dag = None
                unitary = node.op.to_matrix()
                n_qubits = len(node.qargs)
                if (
                    plugin_method.max_qubits is not None and n_qubits > plugin_method.max_qubits
                ) or (plugin_method.min_qubits is not None and n_qubits < plugin_method.min_qubits):
                    method, kwargs = default_method, default_kwargs
                else:
                    method, kwargs = plugin_method, plugin_kwargs
                if method.supports_coupling_map:
                    kwargs["coupling_map"] = (
                        self._coupling_map,
                        [qubit_indices[x] for x in node.qargs],
                    )
                synth_dag = method.run(unitary, **kwargs)
                if synth_dag is None:
                    out_dag.apply_operation_back(node.op, node.qargs, node.cargs, check=False)
                    continue
                if isinstance(synth_dag, DAGCircuit):
                    qubit_map = dict(zip(synth_dag.qubits, node.qargs))
                    for node in synth_dag.topological_op_nodes():
                        out_dag.apply_operation_back(
                            node.op, (qubit_map[x] for x in node.qargs), check=False
                        )
                    out_dag.global_phase += synth_dag.global_phase
                else:
                    node_list, global_phase, gate = synth_dag
                    qubits = node.qargs
                    for (
                        op_name,
                        params,
                        qargs,
                    ) in node_list:
                        if op_name == "USER_GATE":
                            op = gate
                        else:
                            op = GATE_NAME_MAP[op_name](*params)
                        out_dag.apply_operation_back(
                            op,
                            (qubits[x] for x in qargs),
                            check=False,
                        )
                    out_dag.global_phase += global_phase
            else:
                out_dag.apply_operation_back(node.op, node.qargs, node.cargs, check=False)
        return out_dag


def _build_gate_lengths(props=None, target=None):
    """Builds a ``gate_lengths`` dictionary from either ``props`` (BackendV1)
    or ``target`` (BackendV2).

    The dictionary has the form:
    {gate_name: {(qubits,): duration}}
    """
    gate_lengths = {}
    if target is not None:
        for gate, prop_dict in target.items():
            gate_lengths[gate] = {}
            for qubit, gate_props in prop_dict.items():
                if gate_props is not None and gate_props.duration is not None:
                    gate_lengths[gate][qubit] = gate_props.duration
    elif props is not None:
        for gate in props._gates:
            gate_lengths[gate] = {}
            for k, v in props._gates[gate].items():
                length = v.get("gate_length")
                if length:
                    gate_lengths[gate][k] = length[0]
            if not gate_lengths[gate]:
                del gate_lengths[gate]
    return gate_lengths


def _build_gate_errors(props=None, target=None):
    """Builds a ``gate_error`` dictionary from either ``props`` (BackendV1)
    or ``target`` (BackendV2).

    The dictionary has the form:
    {gate_name: {(qubits,): error_rate}}
    """
    gate_errors = {}
    if target is not None:
        for gate, prop_dict in target.items():
            gate_errors[gate] = {}
            for qubit, gate_props in prop_dict.items():
                if gate_props is not None and gate_props.error is not None:
                    gate_errors[gate][qubit] = gate_props.error
    if props is not None:
        for gate in props._gates:
            gate_errors[gate] = {}
            for k, v in props._gates[gate].items():
                error = v.get("gate_error")
                if error:
                    gate_errors[gate][k] = error[0]
            if not gate_errors[gate]:
                del gate_errors[gate]
    return gate_errors


def _build_gate_lengths_by_qubit(props=None, target=None):
    """
    Builds a `gate_lengths` dictionary from either `props` (BackendV1)
    or `target (BackendV2)`.

    The dictionary has the form:
    {(qubits): [Gate, duration]}
    """
    gate_lengths = {}
    if target is not None and target.qargs is not None:
        for qubits in target.qargs:
            names = target.operation_names_for_qargs(qubits)
            operation_and_durations = []
            for name in names:
                operation = target.operation_from_name(name)
                duration = getattr(target[name].get(qubits, None), "duration", None)
                if duration:
                    operation_and_durations.append((operation, duration))
            if operation_and_durations:
                gate_lengths[qubits] = operation_and_durations
    elif props is not None:
        for gate_name, gate_props in props._gates.items():
            gate = GateNameToGate[gate_name]
            for qubits, properties in gate_props.items():
                duration = properties.get("gate_length", [0.0])[0]
                operation_and_durations = (gate, duration)
                if qubits in gate_lengths:
                    gate_lengths[qubits].append(operation_and_durations)
                else:
                    gate_lengths[qubits] = [operation_and_durations]
    return gate_lengths


def _build_gate_errors_by_qubit(props=None, target=None):
    """
    Builds a `gate_error` dictionary from either `props` (BackendV1)
    or `target (BackendV2)`.

    The dictionary has the form:
    {(qubits): [Gate, error]}
    """
    gate_errors = {}
    if target is not None and target.qargs is not None:
        for qubits in target.qargs:
            names = target.operation_names_for_qargs(qubits)
            operation_and_errors = []
            for name in names:
                operation = target.operation_from_name(name)
                error = getattr(target[name].get(qubits, None), "error", None)
                if error:
                    operation_and_errors.append((operation, error))
            if operation_and_errors:
                gate_errors[qubits] = operation_and_errors
    elif props is not None:
        for gate_name, gate_props in props._gates.items():
            gate = GateNameToGate[gate_name]
            for qubits, properties in gate_props.items():
                error = properties.get("gate_error", [0.0])[0]
                operation_and_errors = (gate, error)
                if qubits in gate_errors:
                    gate_errors[qubits].append(operation_and_errors)
                else:
                    gate_errors[qubits] = [operation_and_errors]
    return gate_errors


class DefaultUnitarySynthesis(plugin.UnitarySynthesisPlugin):
    """The default unitary synthesis plugin."""

    @property
    def supports_basis_gates(self):
        return True

    @property
    def supports_coupling_map(self):
        return True

    @property
    def supports_natural_direction(self):
        return True

    @property
    def supports_pulse_optimize(self):
        return True

    @property
    def supports_gate_lengths(self):
        return False

    @property
    def supports_gate_errors(self):
        return False

    @property
    def supports_gate_lengths_by_qubit(self):
        return True

    @property
    def supports_gate_errors_by_qubit(self):
        return True

    @property
    def max_qubits(self):
        return None

    @property
    def min_qubits(self):
        return None

    @property
    def supported_bases(self):
        return None

    @property
    def supports_target(self):
        return True

    def __init__(self):
        super().__init__()
        self._decomposer_cache = {}

    def _decomposer_2q_from_target(self, target, qubits, approximation_degree):
        # we just need 2-qubit decomposers, in any direction.
        # we'll fix the synthesis direction later.
        qubits_tuple = tuple(sorted(qubits))
        reverse_tuple = qubits_tuple[::-1]
        if qubits_tuple in self._decomposer_cache:
            return self._decomposer_cache[qubits_tuple]

        # available instructions on this qubit pair, and their associated property.
        available_2q_basis = {}
        available_2q_props = {}

        # 2q gates sent to 2q decomposers must not have any symbolic parameters.  The
        # gates must be convertable to a numeric matrix. If a basis gate supports an arbitrary
        # angle, we have to choose one angle (or more.)
        def _replace_parameterized_gate(op):
            if isinstance(op, RXXGate) and isinstance(op.params[0], Parameter):
                op = RXXGate(pi / 2)
            elif isinstance(op, RZXGate) and isinstance(op.params[0], Parameter):
                op = RZXGate(pi / 4)
            return op

        try:
            keys = target.operation_names_for_qargs(qubits_tuple)
            for key in keys:
                op = target.operation_from_name(key)
                if not isinstance(op, Gate):
                    continue
                available_2q_basis[key] = _replace_parameterized_gate(op)
                available_2q_props[key] = target[key][qubits_tuple]
        except KeyError:
            pass
        try:
            keys = target.operation_names_for_qargs(reverse_tuple)
            for key in keys:
                if key not in available_2q_basis:
                    op = target.operation_from_name(key)
                    if not isinstance(op, Gate):
                        continue
                    available_2q_basis[key] = _replace_parameterized_gate(op)
                    available_2q_props[key] = target[key][reverse_tuple]
        except KeyError:
            pass
        if not available_2q_basis:
            raise TranspilerError(
                f"Target has no gates available on qubits {qubits} to synthesize over."
            )
        # available decomposition basis on each of the qubits of the pair
        # NOTE: assumes both qubits have the same single-qubit gates
        available_1q_basis = _find_matching_euler_bases(target, qubits_tuple[0])

        # find all decomposers
        # TODO: reduce number of decomposers here somehow
        decomposers = []

        def is_supercontrolled(gate):
            try:
                operator = Operator(gate)
            except QiskitError:
                return False
            kak = TwoQubitWeylDecomposition(operator.data)
            return isclose(kak.a, pi / 4) and isclose(kak.c, 0.0)

        def is_controlled(gate):
            try:
                operator = Operator(gate)
            except QiskitError:
                return False
            kak = TwoQubitWeylDecomposition(operator.data)
            return isclose(kak.b, 0.0) and isclose(kak.c, 0.0)

        # possible supercontrolled decomposers (i.e. TwoQubitBasisDecomposer)
        supercontrolled_basis = {
            k: v for k, v in available_2q_basis.items() if is_supercontrolled(v)
        }
        for basis_1q, basis_2q in product(available_1q_basis, supercontrolled_basis.keys()):
            props = available_2q_props.get(basis_2q)
            if props is None:
                basis_2q_fidelity = 1.0
            else:
                error = getattr(props, "error", 0.0)
                if error is None:
                    error = 0.0
                basis_2q_fidelity = 1 - error
            if approximation_degree is not None:
                basis_2q_fidelity *= approximation_degree
            decomposer = TwoQubitBasisDecomposer(
                supercontrolled_basis[basis_2q],
                euler_basis=basis_1q,
                basis_fidelity=basis_2q_fidelity,
            )
            decomposers.append(decomposer)

        # If our 2q basis gates are a subset of cx, ecr, or cz then we know TwoQubitBasisDecomposer
        # is an ideal decomposition and there is no need to bother calculating the XX embodiments
        # or try the XX decomposer
        if {"cx", "cz", "ecr"}.issuperset(available_2q_basis):
            self._decomposer_cache[qubits_tuple] = decomposers
            return decomposers

        # possible controlled decomposers (i.e. XXDecomposer)
        controlled_basis = {k: v for k, v in available_2q_basis.items() if is_controlled(v)}
        basis_2q_fidelity = {}
        embodiments = {}
        pi2_basis = None
        for k, v in controlled_basis.items():
            strength = 2 * TwoQubitWeylDecomposition(Operator(v).data).a  # pi/2: fully entangling
            # each strength has its own fidelity
            props = available_2q_props.get(k)
            if props is None:
                basis_2q_fidelity[strength] = 1.0
            else:
                error = getattr(props, "error", 0.0)
                if error is None:
                    error = 0.0
                basis_2q_fidelity[strength] = 1 - error
            # rewrite XX of the same strength in terms of it
            embodiment = XXEmbodiments[v.base_class]
            if len(embodiment.parameters) == 1:
                embodiments[strength] = embodiment.assign_parameters([strength])
            else:
                embodiments[strength] = embodiment
            # basis equivalent to CX are well optimized so use for the pi/2 angle if available
            if isclose(strength, pi / 2) and k in supercontrolled_basis:
                pi2_basis = v
        # if we are using the approximation_degree knob, use it to scale already-given fidelities
        if approximation_degree is not None:
            basis_2q_fidelity = {k: v * approximation_degree for k, v in basis_2q_fidelity.items()}
        if basis_2q_fidelity:
            for basis_1q in available_1q_basis:
                if isinstance(pi2_basis, CXGate) and basis_1q == "ZSX":
                    # If we're going to use the pulse optimal decomposition
                    # in TwoQubitBasisDecomposer we need to compute the basis
                    # fidelity to use for the decomposition. Either use the
                    # cx error rate if approximation degree is None, or
                    # the approximation degree value if it's a float
                    if approximation_degree is None:
                        props = target["cx"].get(qubits_tuple)
                        if props is not None:
                            fidelity = 1.0 - getattr(props, "error", 0.0)
                        else:
                            fidelity = 1.0
                    else:
                        fidelity = approximation_degree
                    pi2_decomposer = TwoQubitBasisDecomposer(
                        pi2_basis,
                        euler_basis=basis_1q,
                        basis_fidelity=fidelity,
                        pulse_optimize=True,
                    )
                    embodiments.update({pi / 2: XXEmbodiments[pi2_decomposer.gate.base_class]})
                else:
                    pi2_decomposer = None
                decomposer = XXDecomposer(
                    basis_fidelity=basis_2q_fidelity,
                    euler_basis=basis_1q,
                    embodiments=embodiments,
                    backup_optimizer=pi2_decomposer,
                )
                decomposers.append(decomposer)

        self._decomposer_cache[qubits_tuple] = decomposers
        return decomposers

    def run(self, unitary, **options):
        # Approximation degree is set directly as an attribute on the
        # instance by the UnitarySynthesis pass here as it's not part of
        # plugin interface. However if for some reason it's not set assume
        # it's 1.
        approximation_degree = getattr(self, "_approximation_degree", 1.0)
        basis_gates = options["basis_gates"]
        coupling_map = options["coupling_map"][0]
        natural_direction = options["natural_direction"]
        pulse_optimize = options["pulse_optimize"]
        gate_lengths = options["gate_lengths_by_qubit"]
        gate_errors = options["gate_errors_by_qubit"]
        qubits = options["coupling_map"][1]
        target = options["target"]

        if unitary.shape == (2, 2):
            _decomposer1q = Optimize1qGatesDecomposition(basis_gates, target)
            sequence = _decomposer1q._resynthesize_run(unitary, qubits[0])
            if sequence is None:
                return None
            return _decomposer1q._gate_sequence_to_dag(sequence)
        elif unitary.shape == (4, 4):
            # select synthesizers that can lower to the target
            if target is not None:
                decomposers2q = self._decomposer_2q_from_target(
                    target, qubits, approximation_degree
                )
            else:
                decomposer2q = _decomposer_2q_from_basis_gates(
                    basis_gates, pulse_optimize, approximation_degree
                )
                decomposers2q = [decomposer2q] if decomposer2q is not None else []
            # choose the cheapest output among synthesized circuits
            synth_circuits = []
            # If we have a single TwoQubitBasisDecomposer skip dag creation as we don't need to
            # store and can instead manually create the synthesized gates directly in the output dag
            if len(decomposers2q) == 1 and isinstance(decomposers2q[0], TwoQubitBasisDecomposer):
                preferred_direction = _preferred_direction(
                    decomposers2q[0],
                    qubits,
                    natural_direction,
                    coupling_map,
                    gate_lengths,
                    gate_errors,
                )
                return self._synth_su4_no_dag(
                    unitary, decomposers2q[0], preferred_direction, approximation_degree
                )
            for decomposer2q in decomposers2q:
                preferred_direction = _preferred_direction(
                    decomposer2q, qubits, natural_direction, coupling_map, gate_lengths, gate_errors
                )
                synth_circuit = self._synth_su4(
                    unitary, decomposer2q, preferred_direction, approximation_degree
                )
                synth_circuits.append(synth_circuit)
            synth_circuit = min(
                synth_circuits,
                key=partial(_error, target=target, qubits=tuple(qubits)),
                default=None,
            )
        else:
            from qiskit.synthesis.unitary.qsd import (  # pylint: disable=cyclic-import
                qs_decomposition,
            )

            # only decompose if needed. TODO: handle basis better
            synth_circuit = qs_decomposition(unitary) if (basis_gates or target) else None
        if synth_circuit is None:
            return None
        if isinstance(synth_circuit, DAGCircuit):
            return synth_circuit
        return circuit_to_dag(synth_circuit)

    def _synth_su4_no_dag(self, unitary, decomposer2q, preferred_direction, approximation_degree):
        approximate = not approximation_degree == 1.0
        synth_circ = decomposer2q._inner_decomposer(unitary, approximate=approximate)
        if not preferred_direction:
            return (synth_circ, synth_circ.global_phase, decomposer2q.gate)

        synth_direction = None
        # if the gates in synthesis are in the opposite direction of the preferred direction
        # resynthesize a new operator which is the original conjugated by swaps.
        # this new operator is doubly mirrored from the original and is locally equivalent.
        for op_name, _params, qubits in synth_circ:
            if op_name in {"USER_GATE", "cx"}:
                synth_direction = qubits
        if synth_direction is not None and synth_direction != preferred_direction:
            # TODO: Avoid using a dag to correct the synthesis direction
            return self._reversed_synth_su4(unitary, decomposer2q, approximation_degree)
        return (synth_circ, synth_circ.global_phase, decomposer2q.gate)

    def _synth_su4(self, su4_mat, decomposer2q, preferred_direction, approximation_degree):
        approximate = not approximation_degree == 1.0
        synth_circ = decomposer2q(su4_mat, approximate=approximate, use_dag=True)
        if not preferred_direction:
            return synth_circ
        synth_direction = None
        # if the gates in synthesis are in the opposite direction of the preferred direction
        # resynthesize a new operator which is the original conjugated by swaps.
        # this new operator is doubly mirrored from the original and is locally equivalent.
        for inst in synth_circ.topological_op_nodes():
            if inst.op.num_qubits == 2:
                synth_direction = [synth_circ.find_bit(q).index for q in inst.qargs]
        if synth_direction is not None and synth_direction != preferred_direction:
            return self._reversed_synth_su4(su4_mat, decomposer2q, approximation_degree)
        return synth_circ

    def _reversed_synth_su4(self, su4_mat, decomposer2q, approximation_degree):
        approximate = not approximation_degree == 1.0
        su4_mat_mm = su4_mat.copy()
        su4_mat_mm[[1, 2]] = su4_mat_mm[[2, 1]]
        su4_mat_mm[:, [1, 2]] = su4_mat_mm[:, [2, 1]]
        synth_circ = decomposer2q(su4_mat_mm, approximate=approximate, use_dag=True)
        out_dag = DAGCircuit()
        out_dag.global_phase = synth_circ.global_phase
        out_dag.add_qubits(list(reversed(synth_circ.qubits)))
        flip_bits = out_dag.qubits[::-1]
        for node in synth_circ.topological_op_nodes():
            qubits = tuple(flip_bits[synth_circ.find_bit(x).index] for x in node.qargs)
            out_dag.apply_operation_back(node.op, qubits, check=False)
        return out_dag

Qiskit / qiskit / 9856814802

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