Gradients (`qiskit_algorithms.gradients`)#

Algorithms to calculate the gradient of a quantum circuit.

Base Classes#

`BaseEstimatorGradient`	Base class for an `EstimatorGradient` to compute the gradients of the expectation value.
`BaseQGT`	Base class to computes the Quantum Geometric Tensor (QGT) given a pure, parameterized quantum state.
`BaseSamplerGradient`	Base class for a `SamplerGradient` to compute the gradients of the sampling probability.
`EstimatorGradientResult`	Result of EstimatorGradient.
`SamplerGradientResult`	Result of SamplerGradient.
`QGTResult`	Result of QGT.

Finite Differences#

`FiniteDiffEstimatorGradient`	Compute the gradients of the expectation values by finite difference method [1].
`FiniteDiffSamplerGradient`	Compute the gradients of the sampling probability by finite difference method [1].

Linear Combination of Unitaries#

`LinCombEstimatorGradient`	Compute the gradients of the expectation values.
`LinCombSamplerGradient`	Compute the gradients of the sampling probability.
`LinCombQGT`	Computes the Quantum Geometric Tensor (QGT) given a pure, parameterized quantum state.

Parameter Shift Rules#

`ParamShiftEstimatorGradient`	Compute the gradients of the expectation values by the parameter shift rule [1].
`ParamShiftSamplerGradient`	Compute the gradients of the sampling probability by the parameter shift rule [1].

Quantum Fisher Information#

`QFIResult`	Result of QFI.
`QFI`	Computes the Quantum Fisher Information (QFI) given a pure, parameterized quantum state.

Classical Methods#

`ReverseEstimatorGradient`	Estimator gradients with the classically efficient reverse mode.
`ReverseQGT`	QGT calculation with the classically efficient reverse mode.

Simultaneous Perturbation Stochastic Approximation#

`SPSAEstimatorGradient`	Compute the gradients of the expectation value by the Simultaneous Perturbation Stochastic Approximation (SPSA) [1].
`SPSASamplerGradient`	Compute the gradients of the sampling probability by the Simultaneous Perturbation Stochastic Approximation (SPSA) [1].