RealMcLachlanPrinciple
class qiskit.algorithms.time_evolvers.variational.RealMcLachlanPrinciple(qgt=None, gradient=None)
Bases: RealVariationalPrinciple
Class for a Real McLachlan’s Variational Principle. It aims to minimize the distance between both sides of the Schrödinger equation with a quantum state given as a parametrized trial state. The principle leads to a system of linear equations handled by a linear solver. The real variant means that we consider real time dynamics.
Parameters
- qgt (BaseQGT | None) – Instance of a the GQT class used to compute the QFI. If
Noneprovided,LinCombQGTis used. - gradient (BaseEstimatorGradient | None) – Instance of a class used to compute the state gradient. If
Noneprovided,LinCombEstimatorGradientis used.
Raises
AlgorithmError – If the gradient instance does not contain an estimator.
Methods
evolution_gradient
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
Nonegiven, gradients w.r.t. all parameters will be computed.
Returns
An evolution gradient.
Raises
AlgorithmError – If a gradient job fails.
Return type
np.ndarray