quri_parts.tensornetwork.sampler module

tensor_network_state_probabilities(circuit)

Returns the probabilities of the state.

Parameters:

circuit (ImmutableQuantumCircuit)

Return type:

ndarray[Any, dtype[float64]]

tensor_network_ideal_sample(circuit, shots)

Returns the probabilities multiplied by the specific shot count.

Parameters:
Return type:

core.sampling.MeasurementCounts

tensor_network_sample(circuit, shots, seed=None)

Returns the probabilities multiplied by the specific shot count.

Parameters:
Return type:

core.sampling.MeasurementCounts

create_tensornetwork_ideal_sampler()

Returns a Sampler that uses TensorNetwork simulator for returning the probabilities multiplied by the specific shot count.

Return type:

core.sampling.Sampler

create_tensornetwork_sampler(seed=None)

Returns a Sampler that uses TensorNetwork simulator for returning the samples from a probability distribution.

Parameters:

seed (int | None)

Return type:

core.sampling.Sampler

create_tensornetwork_state_sampler(seed=None)

Returns a Sampler that uses TensorNetwork simulator for returning the samples from a probability distribution.

Parameters:

seed (Optional[int])

Return type:

StateSampler[QuantumStateT]

sample_concurrently(circuit_shots_tuples, executor, concurrency=1, seed=None)
Parameters:

  • circuit_shots_tuples (Iterable[tuple[ImmutableQuantumCircuit, int]])

  • executor (Optional['Executor'])

  • concurrency (int)

  • seed (Optional[int])

Return type:

Iterable[MeasurementCounts]

create_tensornetwork_concurrent_sampler(executor=None, concurrency=1, seed=None)

Returns a ConcurrentSampler that uses TensorNetwork simulator for sampling.

For now, this function works when the executor is defined like below

Examples

>>> with ProcessPoolExecutor(
        max_workers=2, mp_context=get_context("spawn")
    ) as executor:
        sampler = create_tensornetwork_concurrent_sampler(
            executor, 2
        )
        results = list(sampler([(circuit1, 1000), (circuit2, 2000)]))
Parameters:

  • executor (Optional['Executor'])

  • concurrency (int)

  • seed (Optional[int])

Return type:

ConcurrentSampler

create_tensornetwork_general_sampler(seed=None)
Parameters:

seed (int | None)

Return type:

GeneralSampler[QuantumStateT, ParametricQuantumStateT]