ParamShiftEstimatorGradient

class ParamShiftEstimatorGradient(estimator, options=None, derivative_type=DerivativeType.REAL)

Bases: BaseEstimatorGradient

Compute the gradients of the expectation values 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

Parameter

• estimator (BaseEstimator) – The estimator 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

• derivative_type (DerivativeType) –

  The type of derivative. Can be either DerivativeType.REAL DerivativeType.IMAG, or DerivativeType.COMPLEX.

  • DerivativeType.REAL computes \(2 \mathrm{Re}[⟨ψ(ω)|O(θ)|dω ψ(ω)〉]\).

  • DerivativeType.IMAG computes \(2 \mathrm{Im}[⟨ψ(ω)|O(θ)|dω ψ(ω)〉]\).

  • DerivativeType.COMPLEX computes \(2 ⟨ψ(ω)|O(θ)|dω ψ(ω)〉\).

  Defaults to DerivativeType.REAL, as this yields e.g. the commonly-used energy gradient and this type is the only supported type for function-level schemes like finite difference.

Methods

run	Run the job of the estimator gradient on the given circuits.
update_default_options	Update the gradient's default options setting.

Attributes

SUPPORTED_GATES = ['x', 'y', 'z', 'h', 'rx', 'ry', 'rz', 'p', 'cx', 'cy', 'cz', 'ryy', 'rxx', 'rzz', 'rzx']

derivative_type

Return the derivative type (real, imaginary or complex).

Rückgabe

The derivative type.

options

Return the union of estimator 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.

Rückgabe

The gradient default + estimator options.