SPSASamplerGradient
class SPSASamplerGradient(sampler, epsilon, batch_size=1, seed=None, options=None)
Bases: qiskit.algorithms.gradients.base_sampler_gradient.BaseSamplerGradient
Compute the gradients of the sampling probability by the Simultaneous Perturbation Stochastic Approximation (SPSA) [1].
Reference: [1] J. C. Spall, Adaptive stochastic approximation by the simultaneous perturbation method in IEEE Transactions on Automatic Control, vol. 45, no. 10, pp. 1839-1853, Oct 2020, doi: 10.1109/TAC.2000.880982(opens in a new tab).
Parameters
- sampler (BaseSampler) – The sampler used to compute the gradients.
- epsilon (float) – The offset size for the SPSA gradients.
- batch_size (int) – number of gradients to average.
- seed (int | None) – The seed for a random perturbation vector.
- options (Options | None) – Primitive backend runtime options used for circuit execution. The order of priority is: options in
runmethod > gradient’s default options > primitive’s default setting. Higher priority setting overrides lower priority setting
Raises
ValueError – If epsilon is not positive.
Methods
run
SPSASamplerGradient.run(circuits, parameter_values, parameters=None, **options)
Run the job of the sampler gradient on the given circuits.
Parameters
- circuits – The list of quantum circuits to compute the gradients.
- parameter_values – The list of parameter values to be bound to the circuit.
- parameters – The sequence of parameters to calculate only the gradients of the specified parameters. Each sequence of parameters corresponds to a circuit in
circuits. Defaults to None, which means that the gradients of all parameters in each circuit are calculated. - options – Primitive backend runtime options used for circuit execution. The order of priority is: options in
runmethod > gradient’s default options > primitive’s default setting. Higher priority setting overrides lower priority setting
Returns
The job object of the gradients of the sampling probability. The i-th result corresponds to circuits[i] evaluated with parameters bound as parameter_values[i]. The j-th quasi-probability distribution in the i-th result corresponds to the gradients of the sampling probability for the j-th parameter in circuits[i].
Raises
ValueError – Invalid arguments are given.
update_default_options
SPSASamplerGradient.update_default_options(**options)
Update the gradient’s default options setting.
Parameters
**options – The fields to update the default options.
Attributes
options
Return the union of sampler options setting and gradient default options, where, if the same field is set in both, the gradient’s default options override the primitive’s default setting.
Return type
Returns
The gradient default + sampler options.