Sampler
class Sampler(circuits: Iterable[QuantumCircuit] | QuantumCircuit | None = None, parameters: Iterable[Iterable[Parameter]] | None = None, **kwargs)
Bases: qiskit.primitives.base.base_sampler.BaseSampler
Aer implementation of Sampler class.
Run Options
- shots (None or int) – The number of shots. If None, it calculates the probabilities exactly. Otherwise, it samples from multinomial distributions.
- seed (int) – Set a fixed seed for
seed_simulator
. If shots is None, this option is ignored.
Precedence of seeding is as follows:
seed_simulator
in runtime (i.e. in__call__()
)seed
in runtime (i.e. in__call__()
)seed_simulator
ofbackend_options
.- default.
Parameters
- circuits – Circuits to be executed.
- parameters – Parameters of each of the quantum circuits. Defaults to
[circ.parameters for circ in circuits]
. - backend_options – Options passed to AerSimulator.
- transpile_options – Options passed to transpile.
- run_options – Options passed to run.
- skip_transpilation – if True, transpilation is skipped.
Methods
close
Sampler.close()
Close the session and free resources
run
Sampler.run(circuits, parameter_values=None, **run_options)
Run the job of the sampling of bitstrings.
Parameters
- circuits – One of more circuit objects.
- parameter_values – 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.
set_options
Sampler.set_options(**fields)
Set options values for the estimator.
Parameters
**fields – The fields to update the options
Attributes
circuits
Quantum circuits to be sampled.
Returns
The quantum circuits to be sampled.
options
parameters
Parameters of quantum circuits.
Returns
List of the parameters in each quantum circuit.