Sampler

class qiskit.primitives.Sampler(*, options=None)[source]

Bases: BaseSampler[PrimitiveJob[SamplerResult]]

Sampler class.

Sampler is a reference implementation of BaseSampler.

Run Options:
  • shots (None or int) – The number of shots. If None, it calculates the probabilities. Otherwise, it samples from multinomial distributions.

  • seed (np.random.Generator or int) – Set a fixed seed or generator for the multinomial distribution. If shots is None, this option is ignored.

Parameters:

options (dict | None) – Default options.

Raises:

QiskitError – if some classical bits are not used for measurements.

Attributes

circuits

Quantum circuits to be sampled.

Returns:

The quantum circuits to be sampled.

options

Return options values for the estimator.

Returns:

options

parameters

Parameters of quantum circuits.

Returns:

List of the parameters in each quantum circuit.

Methods

run(circuits, parameter_values=None, **run_options)

Run the job of the sampling of bitstrings.

Parameters:
  • circuits (QuantumCircuit | Sequence[QuantumCircuit]) – One of more circuit objects.

  • parameter_values (Sequence[float] | Sequence[Sequence[float]] | None) – Parameters to be bound to the circuit.

  • run_options – Backend runtime options used for circuit execution.

Returns:

The job object of the result of the sampler. The i-th result corresponds to circuits[i] evaluated with parameters bound as parameter_values[i].

Raises:

ValueError – Invalid arguments are given.

Return type:

T

set_options(**fields)

Set options values for the estimator.

Parameters:

**fields – The fields to update the options