Skip to main contentIBM Quantum Documentation
This page is from an old version of Qiskit SDK and does not exist in the latest version. We recommend you migrate to the latest version. See the release notes for more information.

ParamShiftSamplerGradient

class ParamShiftSamplerGradient(sampler, options=None)

GitHub

Bases: qiskit.algorithms.gradients.base_sampler_gradient.BaseSamplerGradient

Compute the gradients of the sampling probability by the parameter shift rule [1].

Reference: [1] Schuld, M., Bergholm, V., Gogolin, C., Izaac, J., and Killoran, N. Evaluating analytic gradients on quantum hardware, DOI

Parameters

  • sampler (BaseSampler) – The sampler used to compute the gradients.
  • options (Options | None) – Primitive backend runtime options used for circuit execution. The order of priority is: options in run method > gradient’s default options > primitive’s default setting. Higher priority setting overrides lower priority setting

Methods

run

ParamShiftSamplerGradient.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 run method > 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

ParamShiftSamplerGradient.update_default_options(**options)

Update the gradient’s default options setting.

Parameters

**options – The fields to update the default options.


Attributes

SUPPORTED_GATES

Default value: ['x', 'y', 'z', 'h', 'rx', 'ry', 'rz', 'p', 'cx', 'cy', 'cz', 'ryy', 'rxx', 'rzz', 'rzx']

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

Options

Returns

The gradient default + sampler options.

Was this page helpful?
Report a bug or request content on GitHub.