NumPyMinimumEigensolver
class NumPyMinimumEigensolver(operator=None, aux_operators=None)
The Numpy Minimum Eigensolver algorithm.
Parameters
- operator (
Union[OperatorBase,LegacyBaseOperator,None]) – Operator instance - aux_operators (
Optional[List[Union[OperatorBase,LegacyBaseOperator,None]]]) – Auxiliary operators to be evaluated at minimum eigenvalue
Attributes
aux_operators
Type: Optional[List[Optional[qiskit.aqua.operators.operator_base.OperatorBase]]]
Returns the auxiliary operators.
Return type
Optional[List[Optional[OperatorBase]]]
operator
Type: Optional[qiskit.aqua.operators.operator_base.OperatorBase]
Return the operator.
Return type
Optional[OperatorBase]
random
Return a numpy random.
Methods
compute_minimum_eigenvalue
NumPyMinimumEigensolver.compute_minimum_eigenvalue(operator=None, aux_operators=None)
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.
Parameters
- 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
Return type
Returns
MinimumEigensolverResult
run
NumPyMinimumEigensolver.run()
Execute the classical algorithm.
Returns
results of an algorithm.
Return type
dict
supports_aux_operators
NumPyMinimumEigensolver.supports_aux_operators()
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.
Return type
bool
Returns
True if aux_operator expectations can be evaluated, False otherwise