NumPyMinimumEigensolver

class NumPyMinimumEigensolver(filter_criterion=None)

Bases: MinimumEigensolver

The NumPy minimum eigensolver algorithm.

Parameters:

filter_criterion (FilterType | None) – 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.

Attributes

filter_criterion

Returns the criterion for filtering eigenstates/eigenvalues.

Methods

compute_minimum_eigenvalue(operator, aux_operators=None)

Computes the minimum eigenvalue. The operator and aux_operators are supplied here. While an operator is required by algorithms, aux_operators are optional.

Parameters:

• operator (BaseOperator) – Qubit operator of the observable.

• aux_operators (List[BaseOperator | None] | Dict[str, BaseOperator] | None) – Optional list of auxiliary operators to be evaluated with the parameters of the minimum eigenvalue main result and their expectation values returned. For instance in chemistry these can be dipole operators and total particle count operators, so we can get values for these at the ground state.

Returns:

A minimum eigensolver result.

Return type:

NumPyMinimumEigensolverResult

classmethod supports_aux_operators()

Whether computing the expectation value of auxiliary operators is supported.

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

Returns:

True if aux_operator expectations can be evaluated, False otherwise

Return type:

bool