# qiskit.aqua.algorithms.NumPyMinimumEigensolver¶

class NumPyMinimumEigensolver(operator=None, aux_operators=None, filter_criterion=None)[ソース]

The Numpy Minimum Eigensolver algorithm.

パラメータ
• operator (Union[OperatorBase, LegacyBaseOperator, None]) – Operator instance

• aux_operators (Optional[List[Union[OperatorBase, LegacyBaseOperator, None]]]) – Auxiliary operators to be evaluated at minimum eigenvalue

• filter_criterion (Optional[Callable[[Union[List, ndarray], float, Optional[List[float]]], bool]]) – callable that allows to filter eigenvalues/eigenstates. The minimum eigensolver is only searching over feasible states and returns an eigenstate that has the smallest eigenvalue among feasible states. The callable has the signature filter(eigenstate, eigenvalue, aux_values) and must return a boolean to indicate whether to consider this value or not. If there is no feasible element, the result can even be empty.

__init__(operator=None, aux_operators=None, filter_criterion=None)[ソース]
パラメータ
• operator (Union[OperatorBase, LegacyBaseOperator, None]) – Operator instance

• aux_operators (Optional[List[Union[OperatorBase, LegacyBaseOperator, None]]]) – Auxiliary operators to be evaluated at minimum eigenvalue

• filter_criterion (Optional[Callable[[Union[List, ndarray], float, Optional[List[float]]], bool]]) – callable that allows to filter eigenvalues/eigenstates. The minimum eigensolver is only searching over feasible states and returns an eigenstate that has the smallest eigenvalue among feasible states. The callable has the signature filter(eigenstate, eigenvalue, aux_values) and must return a boolean to indicate whether to consider this value or not. If there is no feasible element, the result can even be empty.

Methods

 __init__([operator, aux_operators, …]) type operator Union[OperatorBase, LegacyBaseOperator, None] compute_minimum_eigenvalue([operator, …]) Computes minimum eigenvalue. Execute the classical algorithm. Whether computing the expectation value of auxiliary operators is supported.

Attributes

 aux_operators Returns the auxiliary operators. filter_criterion returns the filter criterion if set operator Return the operator. random Return a numpy random.
property aux_operators

Returns the auxiliary operators.

Optional[List[Optional[OperatorBase]]]

compute_minimum_eigenvalue(operator=None, aux_operators=None)[ソース]

Computes minimum eigenvalue. Operator and aux_operators can be supplied here and if not None will override any already set into algorithm so it can be reused with different operators. While an operator is required by algorithms, aux_operators are optional. To 『remove』 a previous aux_operators array use an empty list here.

パラメータ
• operator (Union[OperatorBase, LegacyBaseOperator, None]) – If not None replaces operator in algorithm

• aux_operators (Optional[List[Union[OperatorBase, LegacyBaseOperator, None]]]) – If not None replaces aux_operators in algorithm

MinimumEigensolverResult

MinimumEigensolverResult

property filter_criterion

returns the filter criterion if set

Optional[Callable[[Union[List, ndarray], float, Optional[List[float]]], bool]]

property operator

Return the operator.

Optional[OperatorBase]

property random

Return a numpy random.

run()

Execute the classical algorithm.

results of an algorithm.

dict

classmethod supports_aux_operators()[ソース]

Whether computing the expectation value of auxiliary operators is supported.

If the minimum eigensolver computes an eigenstate of the main operator then it can compute the expectation value of the aux_operators for that state. Otherwise they will be ignored.

bool

True if aux_operator expectations can be evaluated, False otherwise