Source code for qctrlopencontrols.dynamic_decoupling_sequences.dynamic_decoupling_sequence

# Copyright 2021 Q-CTRL
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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Dynamical decoupling module.

from typing import (

import numpy as np

from ..driven_controls.driven_control import DrivenControl
from ..exceptions import ArgumentsValueError
from ..utils import (

[docs]class DynamicDecouplingSequence: r""" Creates a dynamic decoupling sequence. Parameters ---------- duration : float The total time in seconds for the sequence :math:`\tau`. offsets : np.ndarray The times offsets :math:`\{t_j\}` in seconds for the center of pulses. rabi_rotations : np.ndarray The rabi rotation :math:`\omega_j` at each time offset :math:`t_j`. azimuthal_angles : np.ndarray The azimuthal angle :math:`\phi_j` at each time offset :math:`t_j`. detuning_rotations : np.ndarray The detuning rotation :math:`\delta_j` at each time offset :math:`t_j`. name : str, optional Name of the sequence. Defaults to None. Notes ----- Dynamical decoupling sequence (DDS) is canonically defined as a series of :math:`n`-instantaneous unitary operations, often :math:`\pi`-pulses, executed at time offsets :math:`\{t_j\}_{j=1}^n` over the time interval with a total duration :math:`\tau`. The :math:`j`-th operation applied at time :math:`t_j` can be parameterized as .. math:: U_j = \exp\left[-\frac{i}{2}(\omega_j \cos \phi_j \sigma_x + \omega_j\sin \phi_j\sigma_y + \delta_j\sigma_z)\right] \;, Note that in practice all DDSs typically have a :math:`X_{\pi/2}` operation at the start :math:`t = 0` and end :math:`t = \tau` of the sequence. This is because it is assumed that the qubit is initially in the state :math:`|0\rangle` and a superposition needs to be created and removed to make the qubit sensitive to dephasing. """ def __init__( self, duration: float, offsets: np.ndarray, rabi_rotations: np.ndarray, azimuthal_angles: np.ndarray, detuning_rotations: np.ndarray, name: Optional[str] = None, ): check_arguments( duration > 0, "Sequence duration must be above zero.", {"duration": duration}, ) offsets = np.asarray(offsets) check_arguments( np.all((offsets >= 0) & (duration >= offsets)), "Offsets for dynamic decoupling sequence must be between 0 and the sequence " "duration (inclusive). ", {"offsets": offsets, "duration": duration}, ) rabi_rotations = np.asarray(rabi_rotations, dtype=np.float) check_arguments( np.all(rabi_rotations >= 0), "Rabi rotations must be non-negative.", {"rabi_rotations": rabi_rotations}, ) _offset_count = len(offsets) check_arguments( len(rabi_rotations) == _offset_count, "rabi rotations must have the same length as offsets. ", {"offsets": offsets, "rabi_rotations": rabi_rotations}, ) check_arguments( len(azimuthal_angles) == _offset_count, "azimuthal angles must have the same length as offsets. ", {"offsets": offsets, "azimuthal_angles": azimuthal_angles}, ) check_arguments( len(detuning_rotations) == _offset_count, "detuning rotations must have the same length as offsets. ", {"offsets": offsets, "detuning_rotations": detuning_rotations}, ) self.duration = duration self.offsets = offsets self.rabi_rotations = rabi_rotations self.azimuthal_angles = np.asarray(azimuthal_angles, dtype=np.float) self.detuning_rotations = np.asarray(detuning_rotations, dtype=np.float) = name
[docs] def export(self) -> Dict: """ Returns a dictionary for plotting using the qctrl-visualizer package. Returns ------- dict Dictionary with plot data that can be used by the plot_sequences method of the qctrl-visualizer package. It has keywords 'Rabi' and 'Detuning'. """ return { "Rabi": [ {"rotation": rabi * np.exp(1.0j * theta), "offset": offset} for rabi, theta, offset in zip( self.rabi_rotations, self.azimuthal_angles, self.offsets ) ], "Detuning": [ {"rotation": rotation, "offset": offset} for rotation, offset in zip(self.detuning_rotations, self.offsets) ], }
def __repr__(self): """ Returns a string representation for the object. The returned string looks like a valid Python expression that could be used to recreate the object, including default arguments. Returns ------- str String representation of the object including the values of the arguments. """ attributes = [ "duration", "offsets", "rabi_rotations", "azimuthal_angles", "detuning_rotations", "name", ] return create_repr_from_attributes(self, attributes) def __str__(self): """ Prepares a friendly string format for a dynamical decoupling sequence. """ def _array_to_str(arr: np.ndarray) -> str: """ Converts elements of an array to a string. [1, 2] -> "1, 2" """ return ", ".join(arr.astype(str)) sequence_string = list() if is not None: sequence_string.append("{}:".format( sequence_string.append("Duration = {}".format(self.duration)) sequence_string.append( f"Offsets = [{_array_to_str(self.offsets / self.duration)}] x {self.duration}" ) sequence_string.append( f"Rabi Rotations = [{_array_to_str(self.rabi_rotations / np.pi)}] x pi" ) sequence_string.append( f"Azimuthal Angles = [{_array_to_str(self.azimuthal_angles / np.pi)}] x pi" ) sequence_string.append( f"Detuning Rotations = [{_array_to_str(self.detuning_rotations / np.pi)}] x pi" ) return "\n".join(sequence_string)
[docs] def export_to_file( self, filename: str, file_format: str = FileFormat.QCTRL.value, file_type: str = FileType.CSV.value, coordinates: str = Coordinate.CYLINDRICAL.value, maximum_rabi_rate: float = 2 * np.pi, maximum_detuning_rate: float = 2 * np.pi, ) -> None: r""" Prepares and saves the dynamical decoupling sequence in a file. Parameters ---------- filename : str Name and path of the file to save the control into. file_format : str Specified file format for saving the control. Defaults to 'Q-CTRL expanded'; Currently it does not support any other format. For detail of the `Q-CTRL Expanded Format` consult :py:meth:`DrivenControl.export_to_file`. file_type : str, optional One of 'CSV' or 'JSON'. Defaults to 'CSV'. coordinates : str, optional Indicates the co-ordinate system requested. Must be one of 'cylindrical', 'cartesian'; defaults to 'cylindrical' maximum_rabi_rate : float, optional Maximum Rabi Rate; Defaults to :math:`2\pi`. maximum_detuning_rate : float, optional Maximum Detuning Rate; Defaults to :math:`2\pi`. Raises ------ ArgumentsValueError Raised if some of the parameters are invalid. Notes ----- The sequence is converted to a driven control using the maximum rabi and detuning rate. The driven control is then exported. This is done to facilitate a coherent integration with Q-CTRL BLACK OPAL's 1-Qubit workspace. """ convert_dds_to_driven_control( dynamic_decoupling_sequence=self, maximum_rabi_rate=maximum_rabi_rate, maximum_detuning_rate=maximum_detuning_rate,, ).export_to_file( filename=filename, file_format=file_format, file_type=file_type, coordinates=coordinates, )
[docs]def convert_dds_to_driven_control( dynamic_decoupling_sequence: DynamicDecouplingSequence, maximum_rabi_rate: float, maximum_detuning_rate: float, minimum_segment_duration: float = 0.0, name: Optional[str] = None, ) -> DrivenControl: r""" Creates a Driven Control based on the supplied DDS and other relevant information. Currently, pulses that simultaneously contain Rabi and detuning rotations are not supported. Parameters ---------- dynamic_decoupling_sequence : DynamicDecouplingSequence The base DDS. Its offsets should be sorted in ascending order in time. maximum_rabi_rate : float Maximum rabi rate. maximum_detuning_rate : float Maximum detuning rate. minimum_segment_duration : float, optional If set, further restricts the duration of every segment of the Driven Controls. Defaults to 0, in which case it does not affect the duration of the pulses. Must be greater than or equal to 0, if set. name : str, optional Name of the sequence. Defaults to None. Returns ------- DrivenControls The Driven Control that contains the segments corresponding to the Dynamic Decoupling Sequence operation. Raises ------ ArgumentsValueError Raised when an argument is invalid or a valid driven control cannot be created from the sequence parameters, maximum rabi rate and maximum detuning rate provided. Notes ----- Driven pulse is defined as a sequence of control segments. Each segment performs an operation (rotation around one or more axes). While the dynamic decoupling sequence operation contains ideal instant operations, the maximum Rabi (detuning) rate defines a minimum time required to perform a given rotation operation. Therefore, each operation in sequence is converted to a flat-topped control segment with a finite duration. Each offset is taken as the mid-point of the control segment and the width of the segment is determined by (rotation/max_rabi(detuning)_rate). If the sequence contains operations at either of the extreme ends :math:`\tau_0=0` and :math:`\tau_{n+1}=\tau`(duration of the sequence), there will be segments outside the boundary (segments starting before :math:`t<0` or finishing after the sequence duration :math:`t>\tau`). In these cases, the segments on either of the extreme ends are shifted appropriately so that their start/end time falls entirely within the duration of the sequence. Moreover, a check is made to make sure the resulting control segments are non-overlapping. If appropriate control segments cannot be created, the conversion process raises an ArgumentsValueError. """ check_arguments( maximum_detuning_rate > 0, "Maximum detuning rate must be positive.", {"maximum_detuning_rate": maximum_detuning_rate}, ) check_arguments( maximum_rabi_rate > 0, "Maximum rabi rate must be positive.", {"maximum_rabi_rate": maximum_rabi_rate}, ) check_arguments( minimum_segment_duration >= 0, "Minimum segment duration must be greater than or equal to 0.", {"minimum_segment_duration": minimum_segment_duration}, ) sequence_duration = dynamic_decoupling_sequence.duration offsets = dynamic_decoupling_sequence.offsets rabi_rotations = dynamic_decoupling_sequence.rabi_rotations azimuthal_angles = dynamic_decoupling_sequence.azimuthal_angles detuning_rotations = dynamic_decoupling_sequence.detuning_rotations # check if all Rabi rotations are valid (i.e. have positive values) check_arguments( np.all(rabi_rotations >= 0.0), "Sequence contains negative values for Rabi rotations.", {"dynamic_decoupling_sequence": dynamic_decoupling_sequence}, ) # check for valid operation check_arguments( _check_valid_operation( rabi_rotations=rabi_rotations, detuning_rotations=detuning_rotations ), "Sequence operation includes rabi rotation and " "detuning rotation at the same instance.", {"dynamic_decoupling_sequence": dynamic_decoupling_sequence}, extras={ "maximum_rabi_rate": maximum_rabi_rate, "maximum_detuning_rate": maximum_detuning_rate, }, ) if offsets.size == 0: offsets = np.array([0, sequence_duration]) rabi_rotations = np.array([0, 0]) azimuthal_angles = np.array([0, 0]) detuning_rotations = np.array([0, 0]) if offsets[0] != 0: offsets = np.append([0], offsets) rabi_rotations = np.append([0], rabi_rotations) azimuthal_angles = np.append([0], azimuthal_angles) detuning_rotations = np.append([0], detuning_rotations) if offsets[-1] != sequence_duration: offsets = np.append(offsets, [sequence_duration]) rabi_rotations = np.append(rabi_rotations, [0]) azimuthal_angles = np.append(azimuthal_angles, [0]) detuning_rotations = np.append(detuning_rotations, [0]) # check that the offsets are correctly sorted in time if any(np.diff(offsets) <= 0.0): raise ArgumentsValueError( "Pulse timing could not be properly deduced from " "the sequence offsets. Make sure all offsets are " "in increasing order.", {"dynamic_decoupling_sequence": dynamic_decoupling_sequence}, extras={"offsets": offsets}, ) offsets = offsets[np.newaxis, :] rabi_rotations = rabi_rotations[np.newaxis, :] azimuthal_angles = azimuthal_angles[np.newaxis, :] detuning_rotations = detuning_rotations[np.newaxis, :] operations = np.concatenate( (offsets, rabi_rotations, azimuthal_angles, detuning_rotations), axis=0 ) pulse_mid_points = operations[0, :] pulse_start_ends = np.zeros((operations.shape[1], 2)) for op_idx in range(operations.shape[1]): # Pulses that cause no rotations can have 0 duration half_pulse_duration = 0.0 if not np.isclose(operations[1, op_idx], 0.0): # Rabi rotation half_pulse_duration = 0.5 * max( operations[1, op_idx] / maximum_rabi_rate, minimum_segment_duration ) elif not np.isclose(operations[3, op_idx], 0.0): # Detuning rotation half_pulse_duration = 0.5 * max( np.abs(operations[3, op_idx]) / maximum_detuning_rate, minimum_segment_duration, ) pulse_start_ends[op_idx, 0] = pulse_mid_points[op_idx] - half_pulse_duration pulse_start_ends[op_idx, 1] = pulse_mid_points[op_idx] + half_pulse_duration # check if any of the pulses have gone outside the time limit [0, sequence_duration] # if yes, adjust the segment timing if pulse_start_ends[0, 0] < 0.0: translation = 0.0 - (pulse_start_ends[0, 0]) pulse_start_ends[0, :] = pulse_start_ends[0, :] + translation if pulse_start_ends[-1, 1] > sequence_duration: translation = pulse_start_ends[-1, 1] - sequence_duration pulse_start_ends[-1, :] = pulse_start_ends[-1, :] - translation # check if the minimum_segment_duration is respected in the gaps between the pulses # as minimum_segment_duration >= 0, this also excludes overlaps gap_durations = pulse_start_ends[1:, 0] - pulse_start_ends[:-1, 1] if not np.all( np.logical_or( np.greater(gap_durations, minimum_segment_duration), np.isclose(gap_durations, minimum_segment_duration), ) ): raise ArgumentsValueError( "Distance between pulses does not respect minimum_segment_duration. " "Try decreasing the minimum_segment_duration or increasing " "the maximum_rabi_rate or the maximum_detuning_rate.", { "dynamic_decoupling_sequence": dynamic_decoupling_sequence, "maximum_rabi_rate": maximum_rabi_rate, "maximum_detuning_rate": maximum_detuning_rate, "minimum_segment_duration": minimum_segment_duration, }, extras={ "deduced_pulse_start_timing": pulse_start_ends[:, 0], "deduced_pulse_end_timing": pulse_start_ends[:, 1], "gap_durations": gap_durations, }, ) if np.allclose(pulse_start_ends, 0.0): # the original sequence should be a free evolution return DrivenControl( rabi_rates=[0.0], azimuthal_angles=[0.0], detunings=[0.0], durations=[sequence_duration], name=name, ) control_rabi_rates = np.zeros((operations.shape[1] * 2,)) control_azimuthal_angles = np.zeros((operations.shape[1] * 2,)) control_detunings = np.zeros((operations.shape[1] * 2,)) control_durations = np.zeros((operations.shape[1] * 2,)) pulse_segment_idx = 0 for op_idx in range(0, operations.shape[1]): pulse_width = pulse_start_ends[op_idx, 1] - pulse_start_ends[op_idx, 0] control_durations[pulse_segment_idx] = pulse_width if pulse_width > 0.0: if not np.isclose(operations[1, op_idx], 0.0): # Rabi rotation control_rabi_rates[pulse_segment_idx] = ( operations[1, op_idx] / pulse_width ) control_azimuthal_angles[pulse_segment_idx] = operations[2, op_idx] elif not np.isclose(operations[3, op_idx], 0.0): # Detuning rotation control_detunings[pulse_segment_idx] = ( operations[3, op_idx] / pulse_width ) if op_idx != (operations.shape[1] - 1): control_rabi_rates[pulse_segment_idx + 1] = 0.0 control_azimuthal_angles[pulse_segment_idx + 1] = 0.0 control_detunings[pulse_segment_idx + 1] = 0.0 control_durations[pulse_segment_idx + 1] = ( pulse_start_ends[op_idx + 1, 0] - pulse_start_ends[op_idx, 1] ) pulse_segment_idx += 2 # almost there; let us check if there is any segments with durations = 0 control_rabi_rates = control_rabi_rates[control_durations > 0.0] control_azimuthal_angles = control_azimuthal_angles[control_durations > 0.0] control_detunings = control_detunings[control_durations > 0.0] control_durations = control_durations[control_durations > 0.0] return DrivenControl( rabi_rates=control_rabi_rates, azimuthal_angles=control_azimuthal_angles, detunings=control_detunings, durations=control_durations, name=name, )
def _check_valid_operation( rabi_rotations: np.ndarray, detuning_rotations: np.ndarray ) -> bool: """ Private method to check if there is a rabi_rotation and detuning rotation at the same offset. """ rabi_rotation_index = set(np.where(rabi_rotations > 0.0)[0]) detuning_rotation_index = set(np.where(detuning_rotations > 0.0)[0]) return not rabi_rotation_index.intersection(detuning_rotation_index)