NumPyEigensolver

class NumPyEigensolver(k=1, filter_criterion=None)

Bases: Eigensolver

Deprecated: NumPy Eigensolver algorithm.

The NumPyEigensolver class has been superseded by the qiskit.algorithms.eigensolvers.NumPyEigensolver class. This class will be deprecated in a future release and subsequently removed after that.

NumPy Eigensolver computes up to the first \(k\) eigenvalues of a complex-valued square matrix of dimension \(n \times n\), with \(k \leq n\).

Bemerkung

Operators are automatically converted to SciPy’s spmatrix as needed and this conversion can be costly in terms of memory and performance as the operator size, mostly in terms of number of qubits it represents, gets larger.

Veraltet ab Version 0.24.0: The class qiskit.algorithms.eigen_solvers.numpy_eigen_solver.NumPyEigensolver is deprecated as of qiskit-terra 0.24.0. It will be removed no earlier than 3 months after the release date. Instead, use the class qiskit.algorithms.eigensolvers.NumPyEigensolver. See https://qisk.it/algo_migration for a migration guide.

Parameter

• k (int) – How many eigenvalues are to be computed, has a min. value of 1.

• filter_criterion (Callable[[list | np.ndarray, float, ListOrDict[float] | None], bool]) – callable that allows to filter eigenvalues/eigenstates, only feasible eigenstates are returned in the results. The callable has the signature filter(eigenstate, eigenvalue, aux_values) and must return a boolean to indicate whether to keep this value in the final returned result or not. If the number of elements that satisfies the criterion is smaller than k then the returned list has fewer elements and can even be empty.

Methods

compute_eigenvalues	Computes eigenvalues.
supports_aux_operators	Whether computing the expectation value of auxiliary operators is supported.

Attributes

filter_criterion

returns the filter criterion if set

k

returns k (number of eigenvalues requested)