DerivativeBase#

class qiskit.opflow.gradients.DerivativeBase[source]#

Bases: ConverterBase

Deprecated: Base class for differentiating opflow objects.

Converter for differentiating opflow objects and handling things like properly differentiating combo_fn’s and enforcing product rules when operator coefficients are parameterized.

This is distinct from CircuitGradient converters which use quantum techniques such as parameter shifts and linear combination of unitaries to compute derivatives of circuits.

CircuitGradient - uses quantum techniques to get derivatives of circuits DerivativeBase - uses classical techniques to differentiate opflow data structures

Deprecated since version 0.24.0: The class qiskit.opflow.gradients.derivative_base.DerivativeBase is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. For code migration guidelines, visit https://qisk.it/opflow_migration.

Methods

abstract convert(operator, params=None)[source]#
Parameters:
Returns:

An operator whose evaluation yields the gradient, Hessian or QFI.

Raises:

ValueError – If params contains a parameter not present in operator.

Return type:

OperatorBase

gradient_wrapper(operator, bind_params, grad_params=None, backend=None, expectation=None)[source]#

Get a callable function which provides the respective gradient, Hessian or QFI for given parameter values. This callable can be used as gradient function for optimizers.

Parameters:
Returns:

Function to compute a gradient, Hessian or QFI. The function takes an iterable as argument which holds the parameter values.

Return type:

Callable[[Iterable], ndarray]

static parameter_expression_grad(param_expr, param)[source]#

Get the derivative of a parameter expression w.r.t. the given parameter.

Deprecated since version 0.18.0: The method qiskit.opflow.gradients.derivative_base.DerivativeBase.parameter_expression_grad() is deprecated as of qiskit-terra 0.18.0. It will be removed no earlier than 3 months after the release date. Instead, use the ParameterExpression.gradient method.

Parameters:
  • param_expr (ParameterExpression) – The Parameter Expression for which we compute the derivative

  • param (ParameterExpression) – Parameter w.r.t. which we want to take the derivative

Returns:

ParameterExpression representing the gradient of param_expr w.r.t. param

Return type:

ParameterExpression | float