DerivativeBase
class DerivativeBase
Bases: qiskit.opflow.converters.converter_base.ConverterBase
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
Methods Defined Here
convert
abstract DerivativeBase.convert(operator, params=None)
Parameters
- operator (
OperatorBase
) – The operator we are taking the gradient, Hessian or QFI of - params (
Union
[ParameterVector
,ParameterExpression
,List
[ParameterExpression
],None
]) – The parameters we are taking the gradient, Hessian or QFI with respect to.
Return type
Returns
An operator whose evaluation yields the gradient, Hessian or QFI.
Raises
ValueError – If params
contains a parameter not present in operator
.
gradient_wrapper
DerivativeBase.gradient_wrapper(operator, bind_params, grad_params=None, backend=None, expectation=None)
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
- operator (
OperatorBase
) – The operator for which we want to get the gradient, Hessian or QFI. - bind_params (
Union
[ParameterExpression
,ParameterVector
,List
[ParameterExpression
]]) – The operator parameters to which the parameter values are assigned. - grad_params (
Union
[ParameterExpression
,ParameterVector
,List
[ParameterExpression
],Tuple
[ParameterExpression
,ParameterExpression
],List
[Tuple
[ParameterExpression
,ParameterExpression
]],None
]) – The parameters with respect to which we are taking the gradient, Hessian or QFI. If grad_params = None, then grad_params = bind_params - backend (
Union
[Backend
,QuantumInstance
,None
]) – The quantum backend or QuantumInstance to use to evaluate the gradient, Hessian or QFI. - expectation (
Optional
[ExpectationBase
]) – The expectation converter to be used. If none is set then PauliExpectation() is used.
Return type
Callable
[[Iterable
], ndarray
]
Returns
Function to compute a gradient, Hessian or QFI. The function takes an iterable as argument which holds the parameter values.
parameter_expression_grad
static DerivativeBase.parameter_expression_grad(param_expr, param)
Get the derivative of a parameter expression w.r.t. the given parameter.
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
Return type
Union
[ParameterExpression
, float
]
Returns
ParameterExpression representing the gradient of param_expr w.r.t. param