qiskit.transpiler.passes.scheduling.dynamical_decoupling のソースコード

# 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
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"""Dynamical Decoupling insertion pass."""

import itertools
import warnings

import numpy as np
from qiskit.circuit.delay import Delay
from qiskit.circuit.reset import Reset
from qiskit.circuit.library.standard_gates import IGate, UGate, U3Gate
from qiskit.dagcircuit import DAGOpNode, DAGInNode
from qiskit.quantum_info.operators.predicates import matrix_equal
from qiskit.quantum_info.synthesis import OneQubitEulerDecomposer
from qiskit.transpiler.passes.optimization import Optimize1qGates
from qiskit.transpiler.basepasses import TransformationPass
from qiskit.transpiler.exceptions import TranspilerError

[ドキュメント]class DynamicalDecoupling(TransformationPass): """Dynamical decoupling insertion pass. This pass works on a scheduled, physical circuit. It scans the circuit for idle periods of time (i.e. those containing delay instructions) and inserts a DD sequence of gates in those spots. These gates amount to the identity, so do not alter the logical action of the circuit, but have the effect of mitigating decoherence in those idle periods. As a special case, the pass allows a length-1 sequence (e.g. [XGate()]). In this case the DD insertion happens only when the gate inverse can be absorbed into a neighboring gate in the circuit (so we would still be replacing Delay with something that is equivalent to the identity). This can be used, for instance, as a Hahn echo. This pass ensures that the inserted sequence preserves the circuit exactly (including global phase). .. jupyter-execute:: import numpy as np from qiskit.circuit import QuantumCircuit from qiskit.circuit.library import XGate from qiskit.transpiler import PassManager, InstructionDurations from qiskit.transpiler.passes import ALAPSchedule, DynamicalDecoupling from qiskit.visualization import timeline_drawer circ = QuantumCircuit(4) circ.h(0) circ.cx(0, 1) circ.cx(1, 2) circ.cx(2, 3) circ.measure_all() durations = InstructionDurations( [("h", 0, 50), ("cx", [0, 1], 700), ("reset", None, 10), ("cx", [1, 2], 200), ("cx", [2, 3], 300), ("x", None, 50), ("measure", None, 1000)] ) .. jupyter-execute:: # balanced X-X sequence on all qubits dd_sequence = [XGate(), XGate()] pm = PassManager([ALAPSchedule(durations), DynamicalDecoupling(durations, dd_sequence)]) circ_dd = pm.run(circ) timeline_drawer(circ_dd) .. jupyter-execute:: # Uhrig sequence on qubit 0 n = 8 dd_sequence = [XGate()] * n def uhrig_pulse_location(k): return np.sin(np.pi * (k + 1) / (2 * n + 2)) ** 2 spacing = [] for k in range(n): spacing.append(uhrig_pulse_location(k) - sum(spacing)) spacing.append(1 - sum(spacing)) pm = PassManager( [ ALAPSchedule(durations), DynamicalDecoupling(durations, dd_sequence, qubits=[0], spacing=spacing), ] ) circ_dd = pm.run(circ) timeline_drawer(circ_dd) """ def __init__(self, durations, dd_sequence, qubits=None, spacing=None, skip_reset_qubits=True): """Dynamical decoupling initializer. Args: durations (InstructionDurations): Durations of instructions to be used in scheduling. dd_sequence (list[Gate]): sequence of gates to apply in idle spots. qubits (list[int]): physical qubits on which to apply DD. If None, all qubits will undergo DD (when possible). spacing (list[float]): a list of spacings between the DD gates. The available slack will be divided according to this. The list length must be one more than the length of dd_sequence, and the elements must sum to 1. If None, a balanced spacing will be used [d/2, d, d, ..., d, d, d/2]. skip_reset_qubits (bool): if True, does not insert DD on idle periods that immediately follow initialized/reset qubits (as qubits in the ground state are less susceptile to decoherence). """ warnings.warn( "The DynamicalDecoupling class has been supersceded by the " "DynamicalDecouplingPadding class which performs the same function but " "requires scheduling and alignment analysis passes to run prior to it. " "This class will be deprecated in a future release and subsequently " "removed after that.", PendingDeprecationWarning, ) super().__init__() self._durations = durations self._dd_sequence = dd_sequence self._qubits = qubits self._spacing = spacing self._skip_reset_qubits = skip_reset_qubits
[ドキュメント] def run(self, dag): """Run the DynamicalDecoupling pass on dag. Args: dag (DAGCircuit): a scheduled DAG. Returns: DAGCircuit: equivalent circuit with delays interrupted by DD, where possible. Raises: TranspilerError: if the circuit is not mapped on physical qubits. """ if len(dag.qregs) != 1 or dag.qregs.get("q", None) is None: raise TranspilerError("DD runs on physical circuits only.") if dag.duration is None: raise TranspilerError("DD runs after circuit is scheduled.") num_pulses = len(self._dd_sequence) sequence_gphase = 0 if num_pulses != 1: if num_pulses % 2 != 0: raise TranspilerError("DD sequence must contain an even number of gates (or 1).") noop = np.eye(2) for gate in self._dd_sequence: noop = noop.dot(gate.to_matrix()) if not matrix_equal(noop, IGate().to_matrix(), ignore_phase=True): raise TranspilerError("The DD sequence does not make an identity operation.") sequence_gphase = np.angle(noop[0][0]) if self._qubits is None: self._qubits = set(range(dag.num_qubits())) else: self._qubits = set(self._qubits) if self._spacing: if sum(self._spacing) != 1 or any(a < 0 for a in self._spacing): raise TranspilerError( "The spacings must be given in terms of fractions " "of the slack period and sum to 1." ) else: # default to balanced spacing mid = 1 / num_pulses end = mid / 2 self._spacing = [end] + [mid] * (num_pulses - 1) + [end] new_dag = dag.copy_empty_like() qubit_index_map = {qubit: index for index, qubit in enumerate(new_dag.qubits)} index_sequence_duration_map = {} for qubit in new_dag.qubits: physical_qubit = qubit_index_map[qubit] dd_sequence_duration = 0 for gate in self._dd_sequence: gate.duration = self._durations.get(gate, physical_qubit) dd_sequence_duration += gate.duration index_sequence_duration_map[physical_qubit] = dd_sequence_duration for nd in dag.topological_op_nodes(): if not isinstance(nd.op, Delay): new_dag.apply_operation_back(nd.op, nd.qargs, nd.cargs) continue dag_qubit = nd.qargs[0] physical_qubit = qubit_index_map[dag_qubit] if physical_qubit not in self._qubits: # skip unwanted qubits new_dag.apply_operation_back(nd.op, nd.qargs, nd.cargs) continue pred = next(dag.predecessors(nd)) succ = next(dag.successors(nd)) if self._skip_reset_qubits: # discount initial delays if isinstance(pred, DAGInNode) or isinstance(pred.op, Reset): new_dag.apply_operation_back(nd.op, nd.qargs, nd.cargs) continue dd_sequence_duration = index_sequence_duration_map[physical_qubit] slack = nd.op.duration - dd_sequence_duration if slack <= 0: # dd doesn't fit new_dag.apply_operation_back(nd.op, nd.qargs, nd.cargs) continue if num_pulses == 1: # special case of using a single gate for DD u_inv = self._dd_sequence[0].inverse().to_matrix() theta, phi, lam, phase = OneQubitEulerDecomposer().angles_and_phase(u_inv) # absorb the inverse into the successor (from left in circuit) if isinstance(succ, DAGOpNode) and isinstance(succ.op, (UGate, U3Gate)): theta_r, phi_r, lam_r = succ.op.params succ.op.params = Optimize1qGates.compose_u3( theta_r, phi_r, lam_r, theta, phi, lam ) sequence_gphase += phase # absorb the inverse into the predecessor (from right in circuit) elif isinstance(pred, DAGOpNode) and isinstance(pred.op, (UGate, U3Gate)): theta_l, phi_l, lam_l = pred.op.params pred.op.params = Optimize1qGates.compose_u3( theta, phi, lam, theta_l, phi_l, lam_l ) sequence_gphase += phase # don't do anything if there's no single-qubit gate to absorb the inverse else: new_dag.apply_operation_back(nd.op, nd.qargs, nd.cargs) continue # insert the actual DD sequence taus = [int(slack * a) for a in self._spacing] unused_slack = slack - sum(taus) # unused, due to rounding to int multiples of dt middle_index = int((len(taus) - 1) / 2) # arbitrary: redistribute to middle taus[middle_index] += unused_slack # now we add up to original delay duration for tau, gate in itertools.zip_longest(taus, self._dd_sequence): if tau > 0: new_dag.apply_operation_back(Delay(tau), [dag_qubit]) if gate is not None: new_dag.apply_operation_back(gate, [dag_qubit]) new_dag.global_phase = _mod_2pi(new_dag.global_phase + sequence_gphase) return new_dag
def _mod_2pi(angle: float, atol: float = 0): """Wrap angle into interval [-π,π). If within atol of the endpoint, clamp to -π""" wrapped = (angle + np.pi) % (2 * np.pi) - np.pi if abs(wrapped - np.pi) < atol: wrapped = -np.pi return wrapped