Source code for qiskit_ibm_provider.transpiler.passes.scheduling.dynamical_decoupling

# This code is part of Qiskit.
# (C) Copyright IBM 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
# of this source tree or at
# Any modifications or derivative works of this code must retain this
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# that they have been altered from the originals.

"""Dynamical decoupling insertion pass for IBM (dynamic circuit) backends."""

import warnings
from typing import Dict, List, Optional, Union

import numpy as np
import rustworkx as rx
from qiskit.circuit import Qubit, Gate
from qiskit.circuit.delay import Delay
from qiskit.circuit.library.standard_gates import IGate, UGate, U3Gate
from qiskit.circuit.reset import Reset
from qiskit.dagcircuit import DAGCircuit, DAGNode, DAGInNode, DAGOpNode
from qiskit.quantum_info.operators.predicates import matrix_equal
from qiskit.quantum_info.synthesis import OneQubitEulerDecomposer
from qiskit.transpiler.exceptions import TranspilerError
from qiskit.transpiler.instruction_durations import InstructionDurations
from qiskit.transpiler.passes.optimization import Optimize1qGates
from qiskit.transpiler import CouplingMap

from .block_base_padder import BlockBasePadder

[docs]class PadDynamicalDecoupling(BlockBasePadder): """Dynamical decoupling insertion pass for IBM dynamic circuit backends. 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.visualization import timeline_drawer from qiskit_ibm_provider.transpiler.passes.scheduling import ALAPScheduleAnalysis from qiskit_ibm_provider.transpiler.passes.scheduling import PadDynamicalDecoupling circ = QuantumCircuit(4) circ.h(0), 1), 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([ALAPScheduleAnalysis(durations), PadDynamicalDecoupling(durations, dd_sequence)]) circ_dd = circ_dd.draw() .. 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 spacings = [] for k in range(n): spacings.append(uhrig_pulse_location(k) - sum(spacings)) spacings.append(1 - sum(spacings)) pm = PassManager( [ ALAPScheduleAnalysis(durations), PadDynamicalDecoupling(durations, dd_sequence, qubits=[0], spacings=spacings), ] ) circ_dd = circ_dd.draw() .. note:: You need to call :class:`~qiskit_ibm_provider.transpiler.passes.scheduling.ALAPScheduleAnalysis` before running dynamical decoupling to guarantee your circuit satisfies acquisition alignment constraints for dynamic circuit backends. """ def __init__( self, durations: InstructionDurations, dd_sequences: Union[List[Gate], List[List[Gate]]], qubits: Optional[List[int]] = None, spacings: Optional[Union[List[List[float]], List[float]]] = None, skip_reset_qubits: bool = True, pulse_alignment: int = 16, extra_slack_distribution: str = "middle", sequence_min_length_ratios: Optional[Union[int, List[int]]] = None, insert_multiple_cycles: bool = False, coupling_map: CouplingMap = None, alt_spacings: Optional[Union[List[List[float]], List[float]]] = None, schedule_idle_qubits: bool = False, ): """Dynamical decoupling initializer. Args: durations: Durations of instructions to be used in scheduling. dd_sequences: Sequence of gates to apply in idle spots. Alternatively a list of gate sequences may be supplied that will preferentially be inserted if there is a delay of sufficient duration. This may be tuned by the optionally supplied ``sequence_min_length_ratios``. qubits: Physical qubits on which to apply DD. If None, all qubits will undergo DD (when possible). spacings: A list of lists 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]. This spacing only applies to the first subcircuit, if a ``coupling_map`` is specified skip_reset_qubits: If True, does not insert DD on idle periods that immediately follow initialized/reset qubits (as qubits in the ground state are less susceptible to decoherence). pulse_alignment: The hardware constraints for gate timing allocation. This is usually provided from ``backend.configuration().timing_constraints``. If provided, the delay length, i.e. ``spacing``, is implicitly adjusted to satisfy this constraint. extra_slack_distribution: The option to control the behavior of DD sequence generation. The duration of the DD sequence should be identical to an idle time in the scheduled quantum circuit, however, the delay in between gates comprising the sequence should be integer number in units of dt, and it might be further truncated when ``pulse_alignment`` is specified. This sometimes results in the duration of the created sequence being shorter than the idle time that you want to fill with the sequence, i.e. `extra slack`. This option takes following values. * "middle": Put the extra slack to the interval at the middle of the sequence. * "edges": Divide the extra slack as evenly as possible into intervals at beginning and end of the sequence. sequence_min_length_ratios: List of minimum delay length to DD sequence ratio to satisfy in order to insert the DD sequence. For example if the X-X dynamical decoupling sequence is 320dt samples long and the available delay is 384dt it has a ratio of 384dt/320dt=1.2. From the perspective of dynamical decoupling this is likely to add more control noise than decoupling error rate reductions. The defaults value is 2.0. insert_multiple_cycles: If the available duration exceeds 2*sequence_min_length_ratio*duration(dd_sequence) enable the insertion of multiple rounds of the dynamical decoupling sequence in that delay. coupling_map: directed graph representing the coupling map for the device. Specifying a coupling map partitions the device into subcircuits, in order to apply DD sequences with different pulse spacings within each. Currently support 2 subcircuits. alt_spacings: A list of lists of spacings between the DD gates, for the second subcircuit, as determined by the coupling map. If None, a balanced spacing that is staggered with respect to the first subcircuit will be used [d, d, d, ..., d, d, 0]. schedule_idle_qubits: Set to true if you'd like a delay inserted on idle qubits. This is useful for timeline visualizations, but may cause issues for execution on large backends. Raises: TranspilerError: When invalid DD sequence is specified. TranspilerError: When pulse gate with the duration which is non-multiple of the alignment constraint value is found. TranspilerError: When the coupling map is not supported (i.e., if degree > 3) """ super().__init__(schedule_idle_qubits=schedule_idle_qubits) self._durations = durations # Enforce list of DD sequences if dd_sequences: try: iter(dd_sequences[0]) except TypeError: dd_sequences = [dd_sequences] self._dd_sequences = dd_sequences self._qubits = qubits self._skip_reset_qubits = skip_reset_qubits self._alignment = pulse_alignment self._coupling_map = coupling_map self._coupling_coloring = None if spacings is not None: try: iter(spacings[0]) # type: ignore except TypeError: spacings = [spacings] # type: ignore if alt_spacings is not None: try: iter(alt_spacings[0]) # type: ignore except TypeError: alt_spacings = [alt_spacings] # type: ignore self._spacings = spacings self._alt_spacings = alt_spacings if self._spacings and len(self._spacings) != len(self._dd_sequences): raise TranspilerError( "Number of sequence spacings must equal number of DD sequences." ) if self._alt_spacings: if not self._coupling_map: warnings.warn( "Alternate spacings are ignored because a coupling map was not provided" ) elif len(self._alt_spacings) != len(self._dd_sequences): raise TranspilerError( "Number of alternate sequence spacings must equal number of DD sequences." ) self._extra_slack_distribution = extra_slack_distribution self._dd_sequence_lengths: Dict[Qubit, List[List[Gate]]] = {} self._sequence_phase = 0 if sequence_min_length_ratios is None: # Use 2.0 as a sane default self._sequence_min_length_ratios = [2.0 for _ in self._dd_sequences] else: try: iter(sequence_min_length_ratios) # type: ignore except TypeError: sequence_min_length_ratios = [sequence_min_length_ratios] # type: ignore self._sequence_min_length_ratios = sequence_min_length_ratios # type: ignore if len(self._sequence_min_length_ratios) != len(self._dd_sequences): raise TranspilerError( "Number of sequence lengths must equal number of DD sequences." ) self._insert_multiple_cycles = insert_multiple_cycles def _pre_runhook(self, dag: DAGCircuit) -> None: super()._pre_runhook(dag) if self._coupling_map: physical_qubits = [dag.qubits.index(q) for q in dag.qubits] subgraph = self._coupling_map.graph.subgraph(physical_qubits) self._coupling_coloring = rx.graph_greedy_color(subgraph.to_undirected()) if any(c > 1 for c in self._coupling_coloring.values()): raise TranspilerError( "This circuit topology is not supported for staggered dynamical decoupling." "The maximum connectivity is 3 nearest neighbors per qubit." ) spacings_required = self._spacings is None if spacings_required: self._spacings = [] # type: ignore alt_spacings_required = ( self._alt_spacings is None and self._coupling_map is not None ) if alt_spacings_required: self._alt_spacings = [] # type: ignore for seq_idx, seq in enumerate(self._dd_sequences): num_pulses = len(self._dd_sequences[seq_idx]) # Check if physical circuit is given if len(dag.qregs) != 1 or dag.qregs.get("q", None) is None: raise TranspilerError("DD runs on physical circuits only.") # Set default spacing otherwise validate user input if spacings_required: mid = 1 / num_pulses end = mid / 2 self._spacings.append([end] + [mid] * (num_pulses - 1) + [end]) # type: ignore else: if sum(self._spacings[seq_idx]) != 1 or any( # type: ignore a < 0 for a in self._spacings[seq_idx] # type: ignore ): raise TranspilerError( "The spacings must be given in terms of fractions " "of the slack period and sum to 1." ) if self._coupling_map: if alt_spacings_required: mid = 1 / num_pulses self._alt_spacings.append([mid] * num_pulses + [0]) # type: ignore else: if sum(self._alt_spacings[seq_idx]) != 1 or any( # type: ignore a < 0 for a in self._alt_spacings[seq_idx] # type: ignore ): raise TranspilerError( "The spacings must be given in terms of fractions " "of the slack period and sum to 1." ) # Check if DD sequence is identity if num_pulses != 1: if num_pulses % 2 != 0: raise TranspilerError( "DD sequence must contain an even number of gates (or 1)." ) # TODO: this check should use the quantum info package in Qiskit. noop = np.eye(2) for gate in self._dd_sequences[seq_idx]: noop = if not matrix_equal(noop, IGate().to_matrix(), ignore_phase=True): raise TranspilerError( "The DD sequence does not make an identity operation." ) self._sequence_phase = np.angle(noop[0][0]) # Precompute qubit-wise DD sequence length for performance for qubit in dag.qubits: seq_length_ = [] if qubit not in self._dd_sequence_lengths: self._dd_sequence_lengths[qubit] = [] physical_index = dag.qubits.index(qubit) if self._qubits and physical_index not in self._qubits: continue for index, gate in enumerate(seq): try: # Check calibration. gate_length = dag.calibrations[][ (physical_index, gate.params) ] if gate_length % self._alignment != 0: # This is necessary to implement lightweight scheduling logic for this pass. # Usually the pulse alignment constraint and pulse data chunk size take # the same value, however, we can intentionally violate this pattern # at the gate level. For example, we can create a schedule consisting of # a pi-pulse of 32 dt followed by a post buffer, i.e. delay, of 4 dt # on the device with 16 dt constraint. Note that the pi-pulse length # is multiple of 16 dt but the gate length of 36 is not multiple of it. # Such pulse gate should be excluded. raise TranspilerError( f"Pulse gate {} with length non-multiple of {self._alignment} " f"is not acceptable in {self.__class__.__name__} pass." ) except KeyError: gate_length = self._durations.get(gate, physical_index) seq_length_.append(gate_length) # Update gate duration. # This is necessary for current timeline drawer, i.e. scheduled. if hasattr( gate, "to_mutable" ): # TODO this check can be removed after Qiskit 1.0, as it is always True gate = gate.to_mutable() seq[index] = gate gate.duration = gate_length self._dd_sequence_lengths[qubit].append(seq_length_) def _pad( self, block_idx: int, qubit: Qubit, t_start: int, t_end: int, next_node: DAGNode, prev_node: DAGNode, ) -> None: # This routine takes care of the pulse alignment constraint for the DD sequence. # Note that the alignment constraint acts on the t0 of the DAGOpNode. # Now this constrained scheduling problem is simplified to the problem of # finding a delay amount which is a multiple of the constraint value by assuming # that the duration of every DAGOpNode is also a multiple of the constraint value. # # For example, given the constraint value of 16 and XY4 with 160 dt gates. # Here we assume current interval is 992 dt. # # relative spacing := [0.125, 0.25, 0.25, 0.25, 0.125] # slack = 992 dt - 4 x 160 dt = 352 dt # # unconstrained sequence: 44dt-X1-88dt-Y2-88dt-X3-88dt-Y4-44dt # constrained sequence : 32dt-X1-80dt-Y2-80dt-X3-80dt-Y4-32dt + extra slack 48 dt # # Now we evenly split extra slack into start and end of the sequence. # The distributed slack should be multiple of 16. # Start = +16, End += 32 # # final sequence : 48dt-X1-80dt-Y2-80dt-X3-80dt-Y4-64dt / in total 992 dt # # Now we verify t0 of every node starts from multiple of 16 dt. # # X1: 48 dt (3 x 16 dt) # Y2: 48 dt + 160 dt + 80 dt = 288 dt (18 x 16 dt) # Y3: 288 dt + 160 dt + 80 dt = 528 dt (33 x 16 dt) # Y4: 368 dt + 160 dt + 80 dt = 768 dt (48 x 16 dt) # # As you can see, constraints on t0 are all satified without explicit scheduling. time_interval = t_end - t_start if self._qubits and self._block_dag.qubits.index(qubit) not in self._qubits: # Target physical qubit is not the target of this DD sequence. self._apply_scheduled_op( block_idx, t_start, Delay(time_interval, self._block_dag.unit), qubit ) return if ( not isinstance(prev_node, DAGInNode) and self._skip_reset_qubits and isinstance(prev_node.op, Reset) and qubit in prev_node.qargs ): self._dirty_qubits.remove(qubit) if qubit not in self._dirty_qubits: # Previous node is the start edge or reset, i.e. qubit is ground state. self._apply_scheduled_op( block_idx, t_start, Delay(time_interval, self._block_dag.unit), qubit ) return for sequence_idx, _ in enumerate(self._dd_sequences): dd_sequence = self._dd_sequences[sequence_idx] seq_lengths = self._dd_sequence_lengths[qubit][sequence_idx] seq_length = np.sum(seq_lengths) seq_ratio = self._sequence_min_length_ratios[sequence_idx] spacings = self._spacings[sequence_idx] alt_spacings = ( np.asarray(self._alt_spacings[sequence_idx]) if self._coupling_map else None ) # Verify the delay duration exceeds the minimum time to insert if time_interval / seq_length <= seq_ratio: continue if self._insert_multiple_cycles: num_sequences = max(int(time_interval // (seq_length * seq_ratio)), 1) if (num_sequences % 2 == 1) and len(dd_sequence) == 1: warnings.warn( "Sequence would result in an odd number of DD cycles with original DD " "sequence of length 1. This may result in non-identity sequence insertion " "and so are defaulting to 1 cycle insertion." ) num_sequences = 1 else: num_sequences = 1 # multiple dd sequences may be inserted if num_sequences > 1: dd_sequence = list(dd_sequence) * num_sequences seq_lengths = seq_lengths * num_sequences seq_length = np.sum(seq_lengths) spacings = spacings * num_sequences spacings = np.asarray(spacings) / num_sequences slack = time_interval - seq_length sequence_gphase = self._sequence_phase if slack <= 0: continue if len(dd_sequence) == 1: # Special case of using a single gate for DD u_inv = dd_sequence[0].inverse().to_matrix() theta, phi, lam, phase = OneQubitEulerDecomposer().angles_and_phase( u_inv ) if isinstance(next_node, DAGOpNode) and isinstance( next_node.op, (UGate, U3Gate) ): # Absorb the inverse into the successor (from left in circuit) theta_r, phi_r, lam_r = next_node.op.params next_node.op.params = Optimize1qGates.compose_u3( theta_r, phi_r, lam_r, theta, phi, lam ) sequence_gphase += phase elif isinstance(prev_node, DAGOpNode) and isinstance( prev_node.op, (UGate, U3Gate) ): # Absorb the inverse into the predecessor (from right in circuit) theta_l, phi_l, lam_l = prev_node.op.params prev_node.op.params = Optimize1qGates.compose_u3( theta, phi, lam, theta_l, phi_l, lam_l ) sequence_gphase += phase else: # Don't do anything if there's no single-qubit gate to absorb the inverse self._apply_scheduled_op( block_idx, t_start, Delay(time_interval, self._block_dag.unit), qubit, ) return def _constrained_length(values: np.array) -> np.array: return self._alignment * np.floor(values / self._alignment) if self._coupling_map: if self._coupling_coloring[self._dag.qubits.index(qubit)] == 0: sub_spacings = spacings else: sub_spacings = alt_spacings else: sub_spacings = spacings # (1) Compute DD intervals satisfying the constraint taus = _constrained_length(slack * sub_spacings) extra_slack = slack - np.sum(taus) # (2) Distribute extra slack if self._extra_slack_distribution == "middle": mid_ind = int((len(taus) - 1) / 2) to_middle = _constrained_length(extra_slack) taus[mid_ind] += to_middle if extra_slack - to_middle: # If to_middle is not a multiple value of the pulse alignment, # it is truncated to the nearest multiple value and # the rest of slack is added to the end. taus[-1] += extra_slack - to_middle elif self._extra_slack_distribution == "edges": to_begin_edge = _constrained_length(extra_slack / 2) taus[0] += to_begin_edge taus[-1] += extra_slack - to_begin_edge else: raise TranspilerError( f"Option extra_slack_distribution = {self._extra_slack_distribution} is invalid." ) # (3) Construct DD sequence with delays idle_after = t_start dd_ind = 0 # Interleave delays with DD sequence operations for tau_idx, tau in enumerate(taus): if tau > 0: self._apply_scheduled_op( block_idx, idle_after, Delay(tau, self._dag.unit), qubit ) idle_after += tau # Detect if we are on a sequence boundary # If so skip insert of sequence to allow delays to combine # There are two cases. # 1. The number of delays to be inserted is equal to the number of gates. # 2. There is an extra delay inserted after the last operation. # The condition below handles both. seq_length = int(len(taus) / num_sequences) if len(dd_sequence) == len(taus) or tau_idx % seq_length != ( seq_length - 1 ): gate = dd_sequence[dd_ind] gate_length = seq_lengths[dd_ind] self._apply_scheduled_op(block_idx, idle_after, gate, qubit) idle_after += gate_length dd_ind += 1 self._block_dag.global_phase = ( self._block_dag.global_phase + sequence_gphase ) return # DD could not be applied, delay instead self._apply_scheduled_op( block_idx, t_start, Delay(time_interval, self._block_dag.unit), qubit ) return