Quellcode für qiskit.circuit.library.evolved_operator_ansatz

# This code is part of Qiskit.
# (C) Copyright IBM 2021.
# 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.

"""The evolved operator ansatz."""

from __future__ import annotations
from collections.abc import Sequence

import numpy as np

from qiskit.circuit.parameter import Parameter
from qiskit.circuit.quantumregister import QuantumRegister
from qiskit.circuit.quantumcircuit import QuantumCircuit
from qiskit.exceptions import QiskitError
from qiskit.quantum_info import Operator, Pauli, SparsePauliOp
from qiskit.synthesis.evolution import LieTrotter

from .pauli_evolution import PauliEvolutionGate
from .n_local.n_local import NLocal

[Doku]class EvolvedOperatorAnsatz(NLocal): """The evolved operator ansatz.""" def __init__( self, operators=None, reps: int = 1, evolution=None, insert_barriers: bool = False, name: str = "EvolvedOps", parameter_prefix: str | Sequence[str] = "t", initial_state: QuantumCircuit | None = None, flatten: bool | None = None, ): """ Args: operators (BaseOperator | OperatorBase | QuantumCircuit | list | None): The operators to evolve. If a circuit is passed, we assume it implements an already evolved operator and thus the circuit is not evolved again. Can be a single operator (circuit) or a list of operators (and circuits). reps: The number of times to repeat the evolved operators. evolution (EvolutionBase | EvolutionSynthesis | None): A specification of which evolution synthesis to use for the :class:`.PauliEvolutionGate`, if the operator is from :mod:`qiskit.quantum_info` or an opflow converter object if the operator is from :mod:`qiskit.opflow`. Defaults to first order Trotterization. insert_barriers: Whether to insert barriers in between each evolution. name: The name of the circuit. parameter_prefix: Set the names of the circuit parameters. If a string, the same prefix will be used for each parameters. Can also be a list to specify a prefix per operator. initial_state: A :class:`.QuantumCircuit` object to prepend to the circuit. flatten: Set this to ``True`` to output a flat circuit instead of nesting it inside multiple layers of gate objects. By default currently the contents of the output circuit will be wrapped in nested objects for cleaner visualization. However, if you're using this circuit for anything besides visualization its **strongly** recommended to set this flag to ``True`` to avoid a large performance overhead for parameter binding. """ super().__init__( initial_state=initial_state, parameter_prefix=parameter_prefix, reps=reps, insert_barriers=insert_barriers, name=name, flatten=flatten, ) self._operators = None if operators is not None: self.operators = operators self._evolution = evolution # a list of which operators are parameterized, used for internal settings self._ops_are_parameterized = None def _check_configuration(self, raise_on_failure: bool = True) -> bool: """Check if the current configuration is valid.""" if not super()._check_configuration(raise_on_failure): return False if self.operators is None: if raise_on_failure: raise ValueError("The operators are not set.") return False return True @property def num_qubits(self) -> int: if self.operators is None: return 0 if isinstance(self.operators, list) and len(self.operators) > 0: return self.operators[0].num_qubits return self.operators.num_qubits @property def evolution(self): """The evolution converter used to compute the evolution. Returns: EvolutionBase or EvolutionSynthesis: The evolution converter used to compute the evolution. """ if self._evolution is None: # pylint: disable=cyclic-import from qiskit.opflow import PauliTrotterEvolution return PauliTrotterEvolution() return self._evolution @evolution.setter def evolution(self, evol) -> None: """Sets the evolution converter used to compute the evolution. Args: evol (EvolutionBase | EvolutionSynthesis): An evolution synthesis object or opflow converter object to construct the evolution. """ self._invalidate() self._evolution = evol @property def operators(self): """The operators that are evolved in this circuit. Returns: list: The operators to be evolved (and circuits) contained in this ansatz. """ return self._operators @operators.setter def operators(self, operators=None) -> None: """Set the operators to be evolved. operators (Optional[Union[OperatorBase, QuantumCircuit, list]): The operators to evolve. If a circuit is passed, we assume it implements an already evolved operator and thus the circuit is not evolved again. Can be a single operator (circuit) or a list of operators (and circuits). """ operators = _validate_operators(operators) self._invalidate() self._operators = operators self.qregs = [QuantumRegister(self.num_qubits, name="q")] # TODO: the `preferred_init_points`-implementation can (and should!) be improved! @property def preferred_init_points(self): """Getter of preferred initial points based on the given initial state.""" if self._initial_state is None: return None else: # If an initial state was set by the user, then we want to make sure that the VQE does # not start from a random point. Thus, we return an all-zero initial point for the # optimizer which is used (unless it gets overwritten by a higher-priority setting at # runtime of the VQE). # However, in order to determine the correct length, we must build the QuantumCircuit # first, because otherwise the operators may not be set yet. self._build() return np.zeros(self.reps * len(self.operators), dtype=float) def _evolve_operator(self, operator, time): from qiskit.opflow import OperatorBase, EvolutionBase from qiskit.extensions import HamiltonianGate if isinstance(operator, OperatorBase): if not isinstance(self.evolution, EvolutionBase): raise QiskitError( "If qiskit.opflow operators are evolved the evolution must be a " f"qiskit.opflow.EvolutionBase, not a {type(self.evolution)}." ) evolved = self.evolution.convert((time * operator).exp_i()) return evolved.reduce().to_circuit() # if the operator is specified as matrix use exact matrix exponentiation if isinstance(operator, Operator): gate = HamiltonianGate(operator, time) # otherwise, use the PauliEvolutionGate else: evolution = LieTrotter() if self._evolution is None else self._evolution gate = PauliEvolutionGate(operator, time, synthesis=evolution) evolved = QuantumCircuit(operator.num_qubits) if not self.flatten: evolved.append(gate, evolved.qubits) else: evolved.compose(gate.definition, evolved.qubits, inplace=True) return evolved def _build(self): if self._is_built: return # need to check configuration here to ensure the operators are not None self._check_configuration() coeff = Parameter("c") circuits = [] for op in self.operators: # if the operator is already the evolved circuit just append it if isinstance(op, QuantumCircuit): circuits.append(op) else: # check if the operator is just the identity, if yes, skip it if _is_pauli_identity(op): continue evolved = self._evolve_operator(op, coeff) circuits.append(evolved) self.rotation_blocks = [] self.entanglement_blocks = circuits super()._build()
def _validate_operators(operators): if not isinstance(operators, list): operators = [operators] if len(operators) > 1: num_qubits = operators[0].num_qubits if any(operators[i].num_qubits != num_qubits for i in range(1, len(operators))): raise ValueError("All operators must act on the same number of qubits.") return operators def _validate_prefix(parameter_prefix, operators): if isinstance(parameter_prefix, str): return len(operators) * [parameter_prefix] if len(parameter_prefix) != len(operators): raise ValueError("The number of parameter prefixes must match the operators.") return parameter_prefix def _is_pauli_identity(operator): from qiskit.opflow import PauliOp, PauliSumOp if isinstance(operator, PauliSumOp): operator = operator.to_pauli_op() if isinstance(operator, SparsePauliOp): if len(operator.paulis) == 1: operator = operator.paulis[0] # check if the single Pauli is identity below else: return False if isinstance(operator, PauliOp): operator = operator.primitive if isinstance(operator, Pauli): return not np.any(np.logical_or(operator.x, operator.z)) return False