Sampler
class qiskit.primitives.Sampler(*, options=None)
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(opens in a new tab) | 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
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(opens in a new tab)] | Sequence[Sequence[float(opens in a new tab)]] | 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(opens in a new tab) – Invalid arguments are given.
Return type
T
set_options
set_options(**fields)
Set options values for the estimator.
Parameters
**fields – The fields to update the options