common#

Common python dataclasses for multiple backends.

Module Contents#

Classes#

`LatencyCorrection`	Latency correction in seconds for a port-clock combination.
`DistortionCorrection`	Distortion correction information for a port-clock combination.
`ModulationFrequencies`	Modulation frequencies for a port-clock combination.
`MixerCorrections`	Mixer corrections for a port-clock combination.
`HardwareOptions`	Datastructure containing the hardware options for each port-clock combination.
`LocalOscillatorDescription`	Information needed to specify a Local Oscillator in the `CompilationConfig`.
`HardwareDescription`	Specifies a piece of hardware and its instrument-specific settings.
`Connectivity`	Connectivity between ports on the quantum device and on the control hardware.
`HardwareCompilationConfig`	Information required to compile a schedule to the control-hardware layer.

class LatencyCorrection[source]#

Bases: float

Latency correction in seconds for a port-clock combination.

Positive values delay the operations on the corresponding port-clock combination, while negative values shift the operation backwards in time with respect to other operations in the schedule.

Note

If the port-clock combination of a signal is not specified in the corrections, it is set to zero in compilation. The minimum correction over all port-clock combinations is then subtracted to allow for negative latency corrections and to ensure minimal wait time (see determine_relative_latency_corrections()).

Example

Let’s say we have specified two latency corrections in the CompilationConfig:

compilation_config.hardware_options.latency_corrections = {
    "q0:res-q0.ro": LatencyCorrection(-20e-9),
    "q0:mw-q0.01": LatencyCorrection(120e9),
}

In this case, all operations on port "q0:mw" and clock "q0.01" will be delayed by 140 ns with respect to operations on port "q0:res" and clock "q0.ro".

Initialize self. See help(type(self)) for accurate signature.

class DistortionCorrection(**data: Any)[source]#

Bases: quantify_scheduler.structure.model.DataStructure

Distortion correction information for a port-clock combination.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

filter_func: str[source]#: The function applied to the waveforms.

input_var_name: str[source]#: The argument to which the waveforms will be passed in the filter_func.

kwargs: Dict[str, Union[List, quantify_scheduler.structure.types.NDArray]][source]#: The keyword arguments that are passed to the filter_func.

clipping_values: Optional[List][source]#

The optional boundaries to which the corrected pulses will be clipped, upon exceeding.

Example

compilation_config.hardware_options.distortion_corrections = {
    "q0:fl-cl0.baseband": DistortionCorrection(
        filter_func = "scipy.signal.lfilter",
        input_var_name = "x",
        kwargs = {
            "b": [0, 0.25, 0.5],
            "a": [1]
        },
        clipping_values = [-2.5, 2.5]
    )
}

class ModulationFrequencies(**data: Any)[source]#

Bases: quantify_scheduler.structure.model.DataStructure

Modulation frequencies for a port-clock combination.

Example

compilation_config.hardware_options.modulation_frequencies = {
    "q0:res-q0.ro": ModulationFrequencies(
        interm_freq = None,
        lo_freq = 6e9,
    )
}

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

interm_freq: Optional[float][source]#: The intermodulation frequency (IF) used for this port-clock combination.

lo_freq: Optional[float][source]#: The local oscillator frequency (LO) used for this port-clock combination.

class MixerCorrections(**data: Any)[source]#

Bases: quantify_scheduler.structure.model.DataStructure

Mixer corrections for a port-clock combination.

Example

compilation_config.hardware_options.mixer_corrections = {
    "q0:mw-q0.01": MixerCorrections(
        dc_offset_i = -0.0542,
        dc_offset_q = -0.0328,
        amp_ratio = 0.95,
        phase_error_deg= 0.07,
    )
}

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

dc_offset_i: float = 0.0[source]#: The DC offset on the I channel used for this port-clock combination.

dc_offset_q: float = 0.0[source]#: The DC offset on the Q channel used for this port-clock combination.

amp_ratio: float = 1.0[source]#: The mixer gain ratio used for this port-clock combination.

phase_error: float = 0.0[source]#: The mixer phase error used for this port-clock combination.

class HardwareOptions(**data: Any)[source]#

Bases: quantify_scheduler.structure.model.DataStructure

Datastructure containing the hardware options for each port-clock combination.

This datastructure contains the HardwareOptions that are currently shared among the existing backends. Subclassing is required to add backend-specific options, see e.g., QbloxHardwareOptions, ZIHardwareOptions.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

latency_corrections: Optional[Dict[str, LatencyCorrection]][source]#: Dictionary containing the latency corrections (values) that should be applied to operations on a certain port-clock combination (keys).

distortion_corrections: Optional[Dict[str, DistortionCorrection]][source]#: Dictionary containing the distortion corrections (values) that should be applied to waveforms on a certain port-clock combination (keys).

modulation_frequencies: Optional[Dict[str, ModulationFrequencies]][source]#: Dictionary containing the modulation frequencies (values) that should be used for signals on a certain port-clock combination (keys).

mixer_corrections: Optional[Dict[str, MixerCorrections]][source]#: Dictionary containing the mixer corrections (values) that should be used for signals on a certain port-clock combination (keys).

class LocalOscillatorDescription(**data: Any)[source]#

Bases: quantify_scheduler.structure.model.DataStructure

Information needed to specify a Local Oscillator in the CompilationConfig.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

instrument_type: Literal[LocalOscillator][source]#: The field discriminator for this HardwareDescription datastructure.

instrument_name: Optional[str][source]#: The QCoDeS instrument name corresponding to this Local Oscillator.

generic_icc_name: Optional[str][source]#: The name of the GenericInstrumentCoordinatorComponent corresponding to this Local Oscillator.

frequency_param: str = 'frequency'[source]#: The QCoDeS parameter that is used to set the LO frequency.

power_param: str = 'power'[source]#: The QCoDeS parameter that is used to set the LO power.

power: Optional[int][source]#: The power setting for this Local Oscillator.

class HardwareDescription(**data: Any)[source]#

Bases: quantify_scheduler.structure.model.DataStructure

Specifies a piece of hardware and its instrument-specific settings.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

instrument_type: str[source]#: The instrument type.

class Connectivity(**data: Any)[source]#

Bases: quantify_scheduler.structure.model.DataStructure

Connectivity between ports on the quantum device and on the control hardware.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

class HardwareCompilationConfig(**data: Any)[source]#

Bases: quantify_scheduler.structure.model.DataStructure

Information required to compile a schedule to the control-hardware layer.

From a point of view of Compilation this information is needed to convert a schedule defined on a quantum-device layer to compiled instructions that can be executed on the control hardware.

This datastructure defines the overall structure of a HardwareCompilationConfig. Specific hardware backends may customize fields within this structure by inheriting from this class, see e.g., QbloxHardwareCompilationConfig, ZIHardwareCompilationConfig.

Create a new model by parsing and validating input data from keyword arguments.

Raises ValidationError if the input data cannot be parsed to form a valid model.

backend: Callable[[quantify_scheduler.schedules.schedule.Schedule, Any], quantify_scheduler.schedules.schedule.Schedule][source]#: A . separated string specifying the location of the compilation backend this configuration is intended for.

hardware_description: Dict[str, HardwareDescription][source]#: Datastructure describing the control hardware instruments in the setup and their high-level settings.

connectivity: Union[Connectivity, Dict][source]#: Datastructure representing how ports on the quantum device are connected to ports on the control hardware.

hardware_options: Optional[HardwareOptions][source]#: The HardwareOptions used in the compilation from the quantum-device layer to the control-hardware layer.

_import_backend_if_str(fun: Callable[[quantify_scheduler.schedules.schedule.Schedule, Any], quantify_scheduler.schedules.schedule.Schedule]) → Callable[[quantify_scheduler.schedules.schedule.Schedule, Any], quantify_scheduler.schedules.schedule.Schedule][source]#

_latencies_in_hardware_config(connectivity)[source]#

_distortions_in_hardware_config(connectivity)[source]#