Objective function(s)
qiskit_addon_aqc_tensor.objective
Code for building and evaluating objective functions used for AQC parameter optimization.
Currently, this module provides the simplest possible objective function, OneMinusFidelity
.
OneMinusFidelity
class OneMinusFidelity(target, ansatz, settings)[source]
Bases: object
Simplest possible objective function for use with AQC-Tensor.
Its definition is given by Eq. (7) in arXiv:2301.08609v6:
Minimizing this function is equivalent to maximizing the pure-state fidelity between the state prepared by the ansatz circuit at the current parameter point,(, and the target state, .
When called with an ndarray
of parameters, this object will return (objective_value, gradient)
as a tuple[float, numpy.ndarray]
.
Initialize the objective function.
Parameters
- ansatz (
QuantumCircuit
) – Parametrized ansatz circuit. - target (
TensorNetworkState
) – Target state in tensor-network representation. - settings (
TensorNetworkSimulationSettings
) – Tensor network simulation settings.
__call__
__call__(x)[source]
Evaluate (objective_value, gradient)
of function at point x
.
Return type
Parameters
x (ndarray)
target
Type: TensorNetworkState
Target tensor network.