Gradient

Gradient(grad_method='param_shift', **kwargs)

Bases: qiskit.opflow.gradients.gradient_base.GradientBase

Convert an operator expression to the first-order gradient.

Parameters

grad_method (Union[str, CircuitGradient]) – The method used to compute the state/probability gradient. Can be either 'param_shift' or 'lin_comb' or 'fin_diff'. Ignored for gradients w.r.t observable parameters.
kwargs (dict) – Optional parameters for a CircuitGradient

Raises

ValueError – If method != fin_diff and epsilon is not None.

Methods Defined Here

Gradient.convert(operator, params=None)

Parameters

operator (OperatorBase) – The operator we are taking the gradient of.
params (Union[ParameterVector, ParameterExpression, List[ParameterExpression], None]) – The parameters we are taking the gradient with respect to. If not explicitly passed, they are inferred from the operator and sorted by name.

Return type

OperatorBase

Returns

An operator whose evaluation yields the Gradient.

Raises

Gradient.get_gradient(operator, params)

Get the gradient for the given operator w.r.t. the given parameters

Parameters

operator (OperatorBase) – Operator w.r.t. which we take the gradient.
params (Union[ParameterExpression, ParameterVector, List[ParameterExpression]]) – Parameters w.r.t. which we compute the gradient.

Return type

OperatorBase

Returns

Operator which represents the gradient w.r.t. the given params.

Raises

ValueError – If params contains a parameter not present in operator.
OpflowError – If the coefficient of the operator could not be reduced to 1.
OpflowError – If the differentiation of a combo_fn requires JAX but the package is not installed.
TypeError – If the operator does not include a StateFn given by a quantum circuit
Exception – Unintended code is reached
MissingOptionalLibraryError – jax not installed

Returns CircuitGradient.

Return type

CircuitGradient

Returns

CircuitGradient.

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