cirq_google.engine.AbstractProcessor

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An abstract interface for a quantum processor.

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Main aliases

cirq_google.engine.abstract_processor.AbstractProcessor

This quantum processor has the ability to execute single circuits (via the run method), parameter sweeps (via run_sweep), batched lists of circuits (via run_batch), and calibration requests (via run_calibration). Running circuits can also be done using the cirq.Sampler by calling get_sampler.

The processor interface also includes methods to create, list, and remove reservations on the processor for dedicated access. The processor can also list calibration metrics for the processor given a time period.

This is an abstract class. Inheritors should implement abstract methods.

Methods

create_reservation

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@abc.abstractmethod
create_reservation(
    start_time: datetime.datetime,
    end_time: datetime.datetime,
    whitelisted_users: Optional[List[str]] = None
) -> cirq_google.cloud.quantum.QuantumReservation

Creates a reservation on this processor.

Args
start_time	the starting date/time of the reservation.
end_time	the ending date/time of the reservation.
whitelisted_users	a list of emails that are allowed to send programs during this reservation (in addition to users with permission "quantum.reservations.use" on the project).

engine

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@abc.abstractmethod
engine() -> Optional['abstract_engine.AbstractEngine']

Returns the parent Engine object.

Returns
The program's parent Engine.

expected_down_time

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@abc.abstractmethod
expected_down_time() -> 'Optional[datetime.datetime]'

Returns the start of the next expected down time of the processor, if set.

expected_recovery_time

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@abc.abstractmethod
expected_recovery_time() -> 'Optional[datetime.datetime]'

Returns the expected the processor should be available, if set.

get_calibration

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@abc.abstractmethod
get_calibration(
    calibration_timestamp_seconds: int
) -> cirq_google.engine.Calibration

Retrieve metadata about a specific calibration run.

Args
calibration_timestamp_seconds	The timestamp of the calibration in seconds since epoch.

Returns
The calibration data.

get_current_calibration

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@abc.abstractmethod
get_current_calibration() -> Optional[cirq_google.engine.Calibration]

Returns metadata about the current calibration for a processor.

Returns
The calibration data or None if there is no current calibration.

get_device

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@abc.abstractmethod
get_device() -> cirq.Device

Returns a Device created from the processor's device specification.

This method queries the processor to retrieve the device specification, which is then use to create a Device that will validate that operations are supported and use the correct qubits.

Args
gate_sets	An iterable of serializers that can be used in the device.

Returns
A cirq.Devive representing the processor.

get_device_specification

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@abc.abstractmethod
get_device_specification() -> Optional[cirq_google.api.v2.device_pb2.DeviceSpecification]

Returns a device specification proto for use in determining information about the device.

Returns
Device specification proto if present.

get_reservation

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@abc.abstractmethod
get_reservation(
    reservation_id: str
) -> Optional[cirq_google.cloud.quantum.QuantumReservation]

Retrieve a reservation given its id.

get_sampler

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@abc.abstractmethod
get_sampler(
    run_name: str = '', device_config_name: str = ''
) -> 'cg.ProcessorSampler'

Returns a sampler backed by the processor.

Args
run_name	A unique identifier representing an automation run for the processor. An Automation Run contains a collection of device configurations for the processor.
device_config_name	An identifier used to select the processor configuration utilized to run the job. A configuration identifies the set of available qubits, couplers, and supported gates in the processor.

get_schedule

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@abc.abstractmethod
get_schedule(
    from_time: Union[None, datetime.datetime, datetime.timedelta] = datetime.timedelta(),
    to_time: Union[None, datetime.datetime, datetime.timedelta] = datetime.timedelta(weeks=2),
    time_slot_type: Optional[cirq_google.cloud.quantum.QuantumTimeSlot.TimeSlotType] = None
) -> List[cirq_google.cloud.quantum.QuantumTimeSlot]

Retrieves the schedule for a processor.

The schedule may be filtered by time.

Time slot type will be supported in the future.

Args
from_time	Filters the returned schedule to only include entries that end no earlier than the given value. Specified either as an absolute time (datetime.datetime) or as a time relative to now (datetime.timedelta). Defaults to now (a relative time of 0). Set to None to omit this filter.
to_time	Filters the returned schedule to only include entries that start no later than the given value. Specified either as an absolute time (datetime.datetime) or as a time relative to now (datetime.timedelta). Defaults to two weeks from now (a relative time of two weeks). Set to None to omit this filter.
time_slot_type	Filters the returned schedule to only include entries with a given type (e.g. maintenance, open swim). Defaults to None. Set to None to omit this filter.

Returns
Schedule time slots.

health

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@abc.abstractmethod
health() -> str

Returns the current health of processor.

list_calibrations

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@abc.abstractmethod
list_calibrations(
    earliest_timestamp: Optional[Union[datetime.datetime, datetime.date, int]] = None,
    latest_timestamp: Optional[Union[datetime.datetime, datetime.date, int]] = None
) -> List[cirq_google.engine.Calibration]

Retrieve metadata about a specific calibration run.

Args
earliest_timestamp	The earliest timestamp of a calibration to return in UTC.
latest_timestamp	The latest timestamp of a calibration to return in UTC.

Returns
The list of calibration data with the most recent first.

list_reservations

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@abc.abstractmethod
list_reservations(
    from_time: Union[None, datetime.datetime, datetime.timedelta],
    to_time: Union[None, datetime.datetime, datetime.timedelta]
) -> List[cirq_google.cloud.quantum.QuantumReservation]

Retrieves the reservations from a processor.

Only reservations from this processor and project will be returned. The schedule may be filtered by starting and ending time.

Args
from_time	Filters the returned reservations to only include entries that end no earlier than the given value. Specified either as an absolute time (datetime.datetime) or as a time relative to now (datetime.timedelta). Defaults to now (a relative time of 0). Set to None to omit this filter.
to_time	Filters the returned reservations to only include entries that start no later than the given value. Specified either as an absolute time (datetime.datetime) or as a time relative to now (datetime.timedelta). Defaults to two weeks from now (a relative time of two weeks). Set to None to omit this filter.

Returns
A list of reservations.

remove_reservation

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@abc.abstractmethod
remove_reservation(
    reservation_id: str
) -> None

Removes a reservation on this processor.

run

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run(
    program,
    program_id=None,
    job_id=None,
    param_resolver=None,
    repetitions=1,
    program_description=None,
    program_labels=None,
    job_description=None,
    job_labels=None,
    run_name='',
    device_config_name=''
)

Runs the supplied Circuit on this processor.

Args
program	The Circuit to execute. If a circuit is provided, a moment by moment schedule will be used.
program_id	A user-provided identifier for the program. This must be unique within the Google Cloud project being used. If this parameter is not provided, a random id of the format 'prog-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day.
job_id	Job identifier to use. If this is not provided, a random id of the format 'job-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day.
param_resolver	Parameters to run with the program.
repetitions	The number of repetitions to simulate.
program_description	An optional description to set on the program.
program_labels	Optional set of labels to set on the program.
job_description	An optional description to set on the job.
job_labels	Optional set of labels to set on the job.
run_name	A unique identifier representing an automation run for the processor. An Automation Run contains a collection of device configurations for the processor.
device_config_name	An identifier used to select the processor configuration utilized to run the job. A configuration identifies the set of available qubits, couplers, and supported gates in the processor.

Returns
A single Result for this run.

run_async

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run_async(
    program,
    program_id=None,
    job_id=None,
    param_resolver=None,
    repetitions=1,
    program_description=None,
    program_labels=None,
    job_description=None,
    job_labels=None,
    run_name='',
    device_config_name=''
)

Runs the supplied Circuit on this processor.

Args
program	The Circuit to execute. If a circuit is provided, a moment by moment schedule will be used.
program_id	A user-provided identifier for the program. This must be unique within the Google Cloud project being used. If this parameter is not provided, a random id of the format 'prog-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day.
job_id	Job identifier to use. If this is not provided, a random id of the format 'job-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day.
param_resolver	Parameters to run with the program.
repetitions	The number of repetitions to simulate.
program_description	An optional description to set on the program.
program_labels	Optional set of labels to set on the program.
job_description	An optional description to set on the job.
job_labels	Optional set of labels to set on the job.
run_name	A unique identifier representing an automation run for the processor. An Automation Run contains a collection of device configurations for the processor.
device_config_name	An identifier used to select the processor configuration utilized to run the job. A configuration identifies the set of available qubits, couplers, and supported gates in the processor.

Returns
A single Result for this run.

run_batch

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run_batch(
    programs,
    program_id=None,
    job_id=None,
    params_list=None,
    repetitions=1,
    program_description=None,
    program_labels=None,
    job_description=None,
    job_labels=None,
    run_name='',
    device_config_name=''
)

Runs the supplied Circuits on this processor.

This will combine each Circuit provided in programs into a BatchProgram. Each circuit will pair with the associated parameter sweep provided in the params_list. The number of programs is required to match the number of sweeps. This method does not block until a result is returned. However, no results will be available until the entire batch is complete. Args: programs: The Circuits to execute as a batch. program_id: A user-provided identifier for the program. This must be unique within the Google Cloud project being used. If this parameter is not provided, a random id of the format 'prog-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. job_id: Job identifier to use. If this is not provided, a random id of the format 'job-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. params_list: Parameter sweeps to use with the circuits. The number of sweeps should match the number of circuits and will be paired in order with the circuits. If this is None, it is assumed that the circuits are not parameterized and do not require sweeps. repetitions: Number of circuit repetitions to run. Each sweep value of each circuit in the batch will run with the same repetitions. program_description: An optional description to set on the program. program_labels: Optional set of labels to set on the program. job_description: An optional description to set on the job. job_labels: Optional set of labels to set on the job. run_name: A unique identifier representing an automation run for the processor. An Automation Run contains a collection of device configurations for the processor. device_config_name: An identifier used to select the processor configuration utilized to run the job. A configuration identifies the set of available qubits, couplers, and supported gates in the processor. Returns: An AbstractJob. If this is iterated over it returns a list of cirq.Result. All Results for the first circuit are listed first, then the Results for the second, etc. The Results for a circuit are listed in the order imposed by the associated parameter sweep.

run_batch_async

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run_batch_async(
    programs,
    program_id=None,
    job_id=None,
    params_list=None,
    repetitions=1,
    program_description=None,
    program_labels=None,
    job_description=None,
    job_labels=None,
    run_name='',
    device_config_name=''
)

Runs the supplied Circuits on this processor.

This will combine each Circuit provided in programs into a BatchProgram. Each circuit will pair with the associated parameter sweep provided in the params_list. The number of programs is required to match the number of sweeps. This method does not block until a result is returned. However, no results will be available until the entire batch is complete. Args: programs: The Circuits to execute as a batch. program_id: A user-provided identifier for the program. This must be unique within the Google Cloud project being used. If this parameter is not provided, a random id of the format 'prog-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. job_id: Job identifier to use. If this is not provided, a random id of the format 'job-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. params_list: Parameter sweeps to use with the circuits. The number of sweeps should match the number of circuits and will be paired in order with the circuits. If this is None, it is assumed that the circuits are not parameterized and do not require sweeps. repetitions: Number of circuit repetitions to run. Each sweep value of each circuit in the batch will run with the same repetitions. program_description: An optional description to set on the program. program_labels: Optional set of labels to set on the program. job_description: An optional description to set on the job. job_labels: Optional set of labels to set on the job. run_name: A unique identifier representing an automation run for the processor. An Automation Run contains a collection of device configurations for the processor. device_config_name: An identifier used to select the processor configuration utilized to run the job. A configuration identifies the set of available qubits, couplers, and supported gates in the processor. Returns: An AbstractJob. If this is iterated over it returns a list of cirq.Result. All Results for the first circuit are listed first, then the Results for the second, etc. The Results for a circuit are listed in the order imposed by the associated parameter sweep.

run_calibration

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run_calibration(
    layers,
    program_id=None,
    job_id=None,
    program_description=None,
    program_labels=None,
    job_description=None,
    job_labels=None
)

Runs the specified calibrations on the processor.

Each calibration will be specified by a CalibrationLayer that contains the type of the calibrations to run, a Circuit to optimize, and any arguments needed by the calibration routine. Arguments and circuits needed for each layer will vary based on the calibration type. However, the typical calibration routine may require a single moment defining the gates to optimize, for example. Note: this is an experimental API and is not yet fully supported for all users. Args: layers: The layers of calibration to execute as a batch. program_id: A user-provided identifier for the program. This must be unique within the Google Cloud project being used. If this parameter is not provided, a random id of the format 'calibration-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. job_id: Job identifier to use. If this is not provided, a random id of the format 'calibration-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. program_description: An optional description to set on the program. program_labels: Optional set of labels to set on the program. job_description: An optional description to set on the job. job_labels: Optional set of labels to set on the job. By default, this will add a 'calibration' label to the job. Returns: An AbstractJob whose results can be retrieved by calling calibration_results().

run_calibration_async

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run_calibration_async(
    layers,
    program_id=None,
    job_id=None,
    program_description=None,
    program_labels=None,
    job_description=None,
    job_labels=None
)

Runs the specified calibrations on the processor.

Each calibration will be specified by a CalibrationLayer that contains the type of the calibrations to run, a Circuit to optimize, and any arguments needed by the calibration routine. Arguments and circuits needed for each layer will vary based on the calibration type. However, the typical calibration routine may require a single moment defining the gates to optimize, for example. Note: this is an experimental API and is not yet fully supported for all users. Args: layers: The layers of calibration to execute as a batch. program_id: A user-provided identifier for the program. This must be unique within the Google Cloud project being used. If this parameter is not provided, a random id of the format 'calibration-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. job_id: Job identifier to use. If this is not provided, a random id of the format 'calibration-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. program_description: An optional description to set on the program. program_labels: Optional set of labels to set on the program. job_description: An optional description to set on the job. job_labels: Optional set of labels to set on the job. By default, this will add a 'calibration' label to the job. Returns: An AbstractJob whose results can be retrieved by calling calibration_results().

run_sweep

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run_sweep(
    program,
    program_id=None,
    job_id=None,
    params=None,
    repetitions=1,
    program_description=None,
    program_labels=None,
    job_description=None,
    job_labels=None,
    run_name='',
    device_config_name=''
)

Runs the supplied Circuit on this processor.

In contrast to run, this runs across multiple parameter sweeps, and does not block until a result is returned. Args: program: The Circuit to execute. If a circuit is provided, a moment by moment schedule will be used. program_id: A user-provided identifier for the program. This must be unique within the Google Cloud project being used. If this parameter is not provided, a random id of the format 'prog-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. job_id: Job identifier to use. If this is not provided, a random id of the format 'job-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. params: Parameters to run with the program. repetitions: The number of circuit repetitions to run. program_description: An optional description to set on the program. program_labels: Optional set of labels to set on the program. job_description: An optional description to set on the job. job_labels: Optional set of labels to set on the job. run_name: A unique identifier representing an automation run for the processor. An Automation Run contains a collection of device configurations for the processor. device_config_name: An identifier used to select the processor configuration utilized to run the job. A configuration identifies the set of available qubits, couplers, and supported gates in the processor. Returns: An AbstractJob. If this is iterated over it returns a list of cirq.Result, one for each parameter sweep.

run_sweep_async

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run_sweep_async(
    program,
    program_id=None,
    job_id=None,
    params=None,
    repetitions=1,
    program_description=None,
    program_labels=None,
    job_description=None,
    job_labels=None,
    run_name='',
    device_config_name=''
)

Runs the supplied Circuit on this processor.

In contrast to run, this runs across multiple parameter sweeps, and does not block until a result is returned. Args: program: The Circuit to execute. If a circuit is provided, a moment by moment schedule will be used. program_id: A user-provided identifier for the program. This must be unique within the Google Cloud project being used. If this parameter is not provided, a random id of the format 'prog-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. job_id: Job identifier to use. If this is not provided, a random id of the format 'job-################YYMMDD' will be generated, where # is alphanumeric and YYMMDD is the current year, month, and day. params: Parameters to run with the program. repetitions: The number of circuit repetitions to run. program_description: An optional description to set on the program. program_labels: Optional set of labels to set on the program. job_description: An optional description to set on the job. job_labels: Optional set of labels to set on the job. run_name: A unique identifier representing an automation run for the processor. An Automation Run contains a collection of device configurations for the processor. device_config_name: An identifier used to select the processor configuration utilized to run the job. A configuration identifies the set of available qubits, couplers, and supported gates in the processor. Returns: An AbstractJob. If this is iterated over it returns a list of cirq.Result, one for each parameter sweep.

supported_languages

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@abc.abstractmethod
supported_languages() -> List[str]

Returns the list of processor supported program languages.

update_reservation

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@abc.abstractmethod
update_reservation(
    reservation_id: str,
    start_time: Optional[datetime.datetime] = None,
    end_time: Optional[datetime.datetime] = None,
    whitelisted_users: Optional[List[str]] = None
)

Updates a reservation with new information.

Updates a reservation with a new start date, end date, or list of additional users. For each field, it the argument is left as None, it will not be updated.