cirq_google.engine.ProcessorSampler

A wrapper around AbstractProcessor to implement the cirq.Sampler interface.

cirq_google.engine.ProcessorSampler(
    *,
    processor: cg.engine.AbstractProcessor,
    run_name: str = '',
    snapshot_id: str = '',
    device_config_name: str = '',
    max_concurrent_jobs: int = 100,
    jobs_per_batch: int = 1
)

processor AbstractProcessor instance to use.
run_name A unique identifier representing an automation run for the specified processor. An Automation Run contains a collection of device configurations for a processor.
snapshot_id A unique identifier for an immutable snapshot reference.
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.
max_concurrent_jobs The maximum number of jobs to be sent concurrently to the Engine. This client-side throttle can be used to proactively reduce load to the backends and avoid quota violations when pipelining circuit executions.
jobs_per_batch If set to greater than 1, this will batch multiple circuits within the same API call when calling run_batch() or run_batch_async() up to a maximum of jobs_per_batch. Note that actual hardware execution order is not guaranteed if jobs_per_batch > 1. (For instance, the hardware may run all circuits for the first sweep point, then the second point, etc).

ValueError If only one of run_name and device_config_name are specified.

device_config_name

max_concurrent_jobs

processor

run_name

snapshot_id

Methods

run

run(
    program: cirq.AbstractCircuit,
    param_resolver: cirq.ParamResolverOrSimilarType = None,
    repetitions: int = 1
) -> cirq.Result

Samples from the given Circuit.

This mode of operation for a sampler will provide results in the form of measurement outcomes. It will not provide access to state vectors (even if the underlying sampling mechanism is a simulator). This method will substitute parameters in the param_resolver attributes for sympy.Symbols used within the Circuit. This circuit will be executed a number of times specified in the repetitions attribute, though some simulated implementations may instead sample from the final distribution rather than execute the circuit each time.

Args
program The circuit to sample from.
param_resolver Parameters to run with the program.
repetitions The number of times to sample.

Returns
cirq.Result that contains all the measurements for a run.

run_async

run_async(
    program, param_resolver=None, repetitions=1
)

Asynchronously samples from the given Circuit.

Provides measurement outcomes as a cirq.Result object. This interface will operate in a similar way to the run method except for executing asynchronously.

Args
program The circuit to sample from.
param_resolver Parameters to run with the program.
repetitions The number of times to sample.

Returns
Result for a run.

run_batch

View source

run_batch(
    programs, params_list=None, repetitions=1
)

run_batch_async

View source

run_batch_async(
    programs, params_list=None, repetitions=1
)

Runs the supplied circuits asynchronously.

Each circuit provided in programs will pair with the optional associated parameter sweep provided in the params_list, and be run with the associated repetitions provided in repetitions (if repetitions is an integer, then all runs will have that number of repetitions). If params_list is specified, then the number of circuits is required to match the number of sweeps. Similarly, when repetitions is a list, the number of circuits is required to match the length of this list.

By default, this method simply invokes run_sweep sequentially for each (circuit, parameter sweep, repetitions) tuple. Child classes that are capable of sampling batches more efficiently should override it to use other strategies. Note that child classes may have certain requirements that must be met in order for a speedup to be possible, such as a constant number of repetitions being used for all circuits. Refer to the documentation of the child class for any such requirements.

Args
programs The circuits to execute as a batch.
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.
repetitions Number of circuit repetitions to run. Can be specified as a single value to use for all runs, or as a list of values, one for each circuit.

Returns
A list of lists of TrialResults. The outer list corresponds to the circuits, while each inner list contains the TrialResults for the corresponding circuit, in the order imposed by the associated parameter sweep.

Raises
ValueError If length of programs is not equal to the length of params_list or the length of repetitions.

run_sweep

View source

run_sweep(
    program, params, repetitions=1
)

run_sweep_async

View source

run_sweep_async(
    program, params, repetitions=1
)

Asynchronously samples from the given Circuit.

By default, this method invokes run_sweep synchronously and simply exposes its result is an awaitable. Child classes that are capable of true asynchronous sampling should override it to use other strategies.

Args
program The circuit to sample from.
params Parameters to run with the program.
repetitions The number of times to sample.

Returns
Result list for this run; one for each possible parameter resolver.

sample

sample(
    program: cirq.AbstractCircuit,
    *,
    repetitions: int = 1,
    params: cirq.Sweepable = None
) -> pd.DataFrame

Samples the given Circuit, producing a pandas data frame.

This interface will operate in a similar way to the run method except that it returns a pandas data frame rather than a cirq.Result object.

Args
program The circuit to sample from.
repetitions The number of times to sample the program, for each parameter mapping.
params Maps symbols to one or more values. This argument can be a dictionary, a list of dictionaries, a cirq.Sweep, a list of cirq.Sweep, etc. The program will be sampled repetition times for each mapping. Defaults to a single empty mapping.

Returns
A pandas.DataFrame with a row for each sample, and a column for each measurement key as well as a column for each symbolic parameter. Measurement results are stored as a big endian integer representation with one bit for each measured qubit in the key. See cirq.big_endian_int_to_bits and similar functions for how to convert this integer into bits. There is an also index column containing the repetition number, for each parameter assignment.

Raises
ValueError If a supplied sweep is invalid.

Examples

>>> a, b, c = cirq.LineQubit.range(3)
>>> sampler = cirq.Simulator()
>>> circuit = cirq.Circuit(cirq.X(a),
...                        cirq.measure(a, key='out'))
>>> print(sampler.sample(circuit, repetitions=4))
   out
0    1
1    1
2    1
3    1

circuit = cirq.Circuit(cirq.X(a),
                       cirq.CNOT(a, b),
                       cirq.measure(a, b, c, key='out'))
print(sampler.sample(circuit, repetitions=4))
   out
0    6
1    6
2    6
3    6
 
circuit = cirq.Circuit(cirq.X(a)**sympy.Symbol('t'),
                       cirq.measure(a, key='out'))
print(sampler.sample(
    circuit,
    repetitions=3,
    params=[{'t': 0}, {'t': 1}]))
   t  out
0  0    0
1  0    0
2  0    0
0  1    1
1  1    1
2  1    1

sample_expectation_values

sample_expectation_values(
    program: cirq.AbstractCircuit,
    observables: (cirq.PauliSumLike | list[cirq.PauliSumLike]),
    *,
    num_samples: int,
    params: cirq.Sweepable = None,
    permit_terminal_measurements: bool = False
) -> Sequence[Sequence[float]]

Calculates estimated expectation values from samples of a circuit.

Please see also cirq.work.observable_measurement.measure_observables for more control over how to measure a suite of observables.

This method can be run on any device or simulator that supports circuit sampling. Compare with simulate_expectation_values in simulator.py, which is limited to simulators but provides exact results.

Args
program The circuit which prepares a state from which we sample expectation values.
observables A list of observables for which to calculate expectation values.
num_samples The number of samples to take. Increasing this value increases the statistical accuracy of the estimate.
params Parameters to run with the program.
permit_terminal_measurements If the provided circuit ends in a measurement, this method will generate an error unless this is set to True. This is meant to prevent measurements from ruining expectation value calculations.

Returns
A list of expectation-value lists. The outer index determines the sweep, and the inner index determines the observable. For instance, results[1][3] would select the fourth observable measured in the second sweep.

Raises
ValueError If the number of samples was not positive, if empty observables were supplied, or if the provided circuit has terminal measurements and permit_terminal_measurements is true.