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VariationalPrinciple

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

Bases: ABC (opens in a new tab)

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 (opens in a new tab)]) – 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

Returns

Metric tensor.

Raises

AlgorithmError – If a QFI job fails.

Return type

Sequence (opens in a new tab)[float (opens in a new tab)]

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