VariationalPrinciple

class qiskit.algorithms.time_evolvers.variational.VariationalPrinciple(qgt, gradient)

Bases: ABC

A Variational Principle class. It determines the time propagation of parameters in a quantum state provided as a parametrized quantum circuit (ansatz).

qgt

Instance of a class used to compute the GQT.

Type

BaseQGT

gradient

Instance of a class used to compute the state gradient.

Type

BaseEstimatorGradient

Parameters

qgt (BaseQGT) – Instance of a class used to compute the GQT.
gradient (BaseEstimatorGradient) – Instance of a class used to compute the state gradient.

Methods

evolution_gradient

abstract evolution_gradient(hamiltonian, ansatz, param_values, gradient_params=None)

Calculates an evolution gradient according to the rules of this variational principle.

Parameters

hamiltonian (BaseOperator) – Operator used for Variational Quantum Time Evolution.
ansatz (QuantumCircuit) – Quantum state in the form of a parametrized quantum circuit.
param_values (Sequence[float]) – Values of parameters to be bound.
gradient_params (Sequence[Parameter] | None) – List of parameters with respect to which gradients should be computed. If None given, gradients w.r.t. all parameters will be computed.

Returns

An evolution gradient.

Return type

np.ndarray

metric_tensor

metric_tensor(ansatz, param_values)

Calculates a metric tensor according to the rules of this variational principle.

Parameters

ansatz (QuantumCircuit) – Quantum state in the form of a parametrized quantum circuit.
param_values (Sequence[float]) – Values of parameters to be bound.

Returns

Metric tensor.

Raises

AlgorithmError – If a QFI job fails.

Return type

Sequence[float]

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