helpers#
Helper functions for Qblox backend.
Module Contents#
Classes#
Holds and validates frequencies. |
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Simple dataclass that holds immutable frequencies after validation. |
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Operation to indicate the beginning of a loop. |
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Operation to indicate the beginning of a conditional. |
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An operation that signals the end of the current control flow statement. |
Functions#
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Generates an array using the parameters specified in |
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Generates names for the I and Q parts of the complex waveform based on a unique |
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Creates a unique identifier from the waveform data, using a hash. Identical arrays |
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Adds a waveform to the waveform dictionary if it is not yet in there and returns the |
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Takes a dictionary with complex waveforms and generates a new dictionary with |
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Convert time value in s to time in ns, and verify that it is aligned with grid time. |
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Determine whether a time value in seconds is a multiple of the grid time. |
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Converts a phase in degrees to the int arguments the NCO phase instructions expect. |
Converts a frequency in Hz to the int argument the NCO set_freq instruction expects. |
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From known frequency for the local oscillator or known intermodulation frequency, |
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Generates a mapping that specifies which port-clock combinations belong to which |
Traverses the schedule and generates OpInfo objects for every pulse and |
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Helper method to calculate the offset from mV or V. |
Raises an error stating that only one scope mode acquisition can be used per module. |
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Generate a new-style QbloxHardwareCompilationConfig from an old-style hardware config. |
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Check if the operation is a square pulse. |
Convert a fine delay value in seconds to an integer value for Q1ASM. |
- generate_waveform_data(data_dict: dict, sampling_rate: float, duration: float | None = None) numpy.ndarray [source]#
Generates an array using the parameters specified in
data_dict
.- Parameters:
data_dict (dict) – The dictionary that contains the values needed to parameterize the waveform.
data_dict['wf_func']
is then called to calculate the values.sampling_rate (float) – The sampling rate used to generate the time axis values.
duration (float or None, optional) – The duration of the waveform in seconds. This parameter can be used if
data_dict
does not contain a'duration'
key. By default None.
- Returns:
wf_data – The (possibly complex) values of the generated waveform. The number of values is determined by rounding to the nearest integer.
- Return type:
np.ndarray
- Raises:
TypeError – If
data_dict
does not contain a'duration'
entry andduration is None
.
- generate_waveform_names_from_uuid(uuid: object) tuple[str, str] [source]#
Generates names for the I and Q parts of the complex waveform based on a unique identifier for the pulse/acquisition.
- Parameters:
uuid – A unique identifier for a pulse/acquisition.
- Returns:
uuid_I – Name for the I waveform.
uuid_Q – Name for the Q waveform.
- generate_uuid_from_wf_data(wf_data: numpy.ndarray, decimals: int = 12) str [source]#
Creates a unique identifier from the waveform data, using a hash. Identical arrays yield identical strings within the same process.
- Parameters:
wf_data – The data to generate the unique id for.
decimals – The number of decimal places to consider.
- Returns:
A unique identifier.
- add_to_wf_dict_if_unique(wf_dict: dict[str, Any], waveform: numpy.ndarray) int [source]#
Adds a waveform to the waveform dictionary if it is not yet in there and returns the uuid and index. If it is already present it simply returns the uuid and index.
- Parameters:
wf_dict – The waveform dict in the format expected by the sequencer.
waveform – The waveform to add.
- Returns:
dict[str, Any] – The (updated) wf_dict.
str – The uuid of the waveform.
int – The index.
- generate_waveform_dict(waveforms_complex: dict[str, numpy.ndarray]) dict[str, dict] [source]#
Takes a dictionary with complex waveforms and generates a new dictionary with real valued waveforms with a unique index, as required by the hardware.
- Parameters:
waveforms_complex – Dictionary containing the complex waveforms. Keys correspond to a unique identifier, value is the complex waveform.
- Returns:
A dictionary with as key the unique name for that waveform, as value another dictionary containing the real-valued data (list) as well as a unique index. Note that the index of the Q waveform is always the index of the I waveform +1.
- Return type:
Examples
import numpy as np from quantify_scheduler.backends.qblox.helpers import generate_waveform_dict complex_waveforms = {12345: np.array([1, 2])} generate_waveform_dict(complex_waveforms) # {'12345_I': {'data': [1, 2], 'index': 0}, # '12345_Q': {'data': [0, 0], 'index': 1}}
{'12345_I': {'data': [1, 2], 'index': 0}, '12345_Q': {'data': [0, 0], 'index': 1}}
- to_grid_time(time: float, grid_time_ns: int = constants.GRID_TIME) int [source]#
Convert time value in s to time in ns, and verify that it is aligned with grid time.
Takes a float value representing a time in seconds as used by the schedule, and returns the integer valued time in nanoseconds that the sequencer uses.
The time value needs to be aligned with grid time, i.e., needs to be a multiple of
GRID_TIME
, within a tolerance of 1 picosecond.- Parameters:
time – A time value in seconds.
grid_time_ns – The grid time to use in nanoseconds.
- Returns:
The integer valued nanosecond time.
- Raises:
ValueError – If
time
is not a multiple ofGRID_TIME
within the tolerance.
- is_multiple_of_grid_time(time: float, grid_time_ns: int = constants.GRID_TIME) bool [source]#
Determine whether a time value in seconds is a multiple of the grid time.
Within a tolerance as defined by
to_grid_time()
.- Parameters:
time – A time value in seconds.
grid_time_ns – The grid time to use in nanoseconds.
- Returns:
True
iftime
is a multiple of the grid time,False
otherwise.
- get_nco_phase_arguments(phase_deg: float) int [source]#
Converts a phase in degrees to the int arguments the NCO phase instructions expect. We take
phase_deg
modulo 360 to account for negative phase and phase larger than 360.- Parameters:
phase_deg – The phase in degrees
- Returns:
The int corresponding to the phase argument.
- get_nco_set_frequency_arguments(frequency_hz: float) int [source]#
Converts a frequency in Hz to the int argument the NCO set_freq instruction expects.
- Parameters:
frequency_hz – The frequency in Hz.
- Returns:
The frequency expressed in steps for the NCO set_freq instruction.
- Raises:
ValueError – If the frequency_hz is out of range.
- class ValidatedFrequencies[source]#
Simple dataclass that holds immutable frequencies after validation.
- determine_clock_lo_interm_freqs(freqs: Frequencies, downconverter_freq: float | None = None, mix_lo: bool | None = True) ValidatedFrequencies [source]#
From known frequency for the local oscillator or known intermodulation frequency, determine any missing frequency, after optionally applying
downconverter_freq
to the clock frequency.If
mix_lo
isTrue
, the following relation is obeyed: \(f_{RF} = f_{LO} + f_{IF}\).If
mix_lo
isFalse
, \(f_{RF} = f_{LO}\) is upheld.Warning
Using
downconverter_freq
requires custom Qblox hardware, do not use otherwise.- Parameters:
freqs (Frequencies) – Frequencies object containing clock, local oscillator (LO) and Intermodulation frequency (IF), the frequency of the numerically controlled oscillator (NCO).
downconverter_freq (Optional[float]) – Frequency for downconverting the clock frequency, using: \(f_\mathrm{out} = f_\mathrm{downconverter} - f_\mathrm{in}\).
mix_lo (bool) – Flag indicating whether IQ mixing is enabled with the LO.
- Returns:
ValidatedFrequencies
object containing the determined LO and IF frequencies and the optionally downconverted clock frequency.- Warns:
RuntimeWarning – In case
downconverter_freq
is set equal to 0, warns to unset vianull
/None
instead.RuntimeWarning – In case LO is overridden to clock due to
mix_lo
being False
- Raises:
ValueError – In case
downconverter_freq
is less than 0.ValueError – In case
downconverter_freq
is less thanclock_freq
.ValueError – In case
mix_lo
isTrue
and neither LO frequency nor IF has been supplied.ValueError – In case
mix_lo
isTrue
and both LO frequency and IF have been supplied and do not adhere to \(f_{RF} = f_{LO} + f_{IF}\).
- generate_port_clock_to_device_map(device_compilers: dict[str, Any]) dict[str, str] [source]#
Generates a mapping that specifies which port-clock combinations belong to which device.
Here, device means a top-level entry in the hardware config, e.g. a Cluster, not which module within the Cluster.
Each port-clock combination may only occur once.
- Parameters:
device_compilers – Dictionary containing compiler configs.
- Returns:
A dictionary with as key a tuple representing a port-clock combination, and as value the name of the device. Note that multiple port-clocks may point to the same device.
- Raises:
ValueError – If a port-clock combination occurs multiple times in the hardware configuration.
- class LoopBegin(repetitions: int, t0: float = 0)[source]#
Bases:
quantify_scheduler.operations.operation.Operation
Operation to indicate the beginning of a loop.
- class ConditionalBegin(qubit_name: str, feedback_trigger_address: int, feedback_trigger_invert: bool, feedback_trigger_count: int, t0: float)[source]#
Bases:
quantify_scheduler.operations.operation.Operation
Operation to indicate the beginning of a conditional.
- Parameters:
qubit_name – The name of the qubit to condition on.
feedback_trigger_address – Feedback trigger address
t0 – Time offset, by default 0
- _get_control_flow_begin(control_flow_operation: quantify_scheduler.operations.control_flow_library.ControlFlowOperation) quantify_scheduler.operations.operation.Operation [source]#
- class _ControlFlowReturn(t0: float = 0)[source]#
Bases:
quantify_scheduler.operations.operation.Operation
An operation that signals the end of the current control flow statement.
Cannot be added to Schedule manually.
- Parameters:
t0 (float, optional) – time offset, by default 0
- _get_control_flow_end(control_flow_operation: quantify_scheduler.operations.control_flow_library.ControlFlowOperation) quantify_scheduler.operations.operation.Operation [source]#
- _get_list_of_operations_for_op_info_creation(operation: quantify_scheduler.operations.operation.Operation | quantify_scheduler.schedules.schedule.Schedule, time_offset: float, accumulator: list[tuple[float, quantify_scheduler.operations.operation.Operation]]) None [source]#
- assign_pulse_and_acq_info_to_devices(schedule: quantify_scheduler.schedules.schedule.Schedule, device_compilers: dict[str, quantify_scheduler.backends.qblox.instrument_compilers.ClusterCompiler]) None [source]#
Traverses the schedule and generates OpInfo objects for every pulse and acquisition, and assigns it to the correct ClusterCompiler.
- Parameters:
schedule – The schedule to extract the pulse and acquisition info from.
device_compilers – Dictionary containing InstrumentCompilers as values and their names as keys.
- Raises:
RuntimeError – This exception is raised then the function encountered an operation that has no pulse or acquisition info assigned to it.
KeyError – This exception is raised when attempting to assign a pulse with a port-clock combination that is not defined in the hardware configuration.
KeyError – This exception is raised when attempting to assign an acquisition with a port-clock combination that is not defined in the hardware configuration.
- calc_from_units_volt(voltage_range: quantify_scheduler.backends.types.qblox.BoundedParameter, name: str, param_name: str, offset: float | None) float | None [source]#
Helper method to calculate the offset from mV or V. Then compares to given voltage range, and throws a ValueError if out of bounds.
- Parameters:
voltage_range – The range of the voltage levels of the device used.
name – The name of the device used.
param_name – The name of the offset parameter this method is using.
offset – The value of the offset parameter this method is using.
- Returns:
The normalized offsets.
- Raises:
RuntimeError – When a unit range is given that is not supported, or a value is given that falls outside the allowed range.
- single_scope_mode_acquisition_raise(sequencer_0: int, sequencer_1: int, module_name: str) None [source]#
Raises an error stating that only one scope mode acquisition can be used per module.
- Parameters:
sequencer_0 – First sequencer which attempts to use the scope mode acquisition.
sequencer_1 – Second sequencer which attempts to use the scope mode acquisition.
module_name – Name of the module.
- Raises:
ValueError – Always raises the error message.
- _generate_new_style_hardware_compilation_config(old_style_config: dict) dict [source]#
Generate a new-style QbloxHardwareCompilationConfig from an old-style hardware config.
- Parameters:
old_style_config – Old-style hardware config.
- Returns:
New-style hardware compilation config dictionary.
- Return type:
- is_square_pulse(operation: quantify_scheduler.operations.operation.Operation | quantify_scheduler.schedules.schedule.Schedule) bool [source]#
Check if the operation is a square pulse.
- Parameters:
operation – The operation to check.
- Returns:
True if the operation is a square pulse, False otherwise.