LatticeModelProblem#
- class LatticeModelProblem(hamiltonian)[fuente]#
Bases:
BaseProblem
A lattice model problem.
This class specifically deals with handling of
LatticeModel
type hamiltonians.The following attributes can be read and updated once the
LatticeModelProblem
object has been constructed.- properties#
a container for additional observable operator factories.
- Parámetros:
hamiltonian (LatticeModel) – A lattice model class to create second quantized operators.
- Muestra:
TypeError – if the provided
hamiltonian
is not of typeLatticeModel
.
Attributes
- hamiltonian#
Returns the hamiltonian wrapped by this problem.
Methods
- get_default_filter_criterion()#
Returns a default filter criterion method to filter the eigenvalues computed by the eigen solver. For more information see also
filter_criterion()
.In the fermionic case the default filter ensures that the number of particles is being preserved.
- get_tapered_mapper(mapper)#
Builds a
TaperedQubitMapper
from one of the mappers. This simplifies the identification of the Pauli operator symmetries and of the symmetry sector in which lies the solution of the problem.- Parámetros:
mapper (QubitMapper) –
QubitMapper
object implementing the mapping of second quantized operators to Pauli operators.- Muestra:
ValueError – If the mapper is a
TaperedQubitMapper
.- Devuelve:
A
TaperedQubitMapper
with pre-built symmetry specifications.- Tipo del valor devuelto:
- interpret(raw_result)[fuente]#
Interprets a raw result in the context of this transformation.
- Parámetros:
raw_result (EigenstateResult | EigensolverResult | MinimumEigensolverResult) – a raw result to be interpreted
- Devuelve:
A lattice model result.
- Tipo del valor devuelto:
- second_q_ops()#
Returns the second quantized operators associated with this problem.
- Devuelve:
A tuple, with the first object being the main operator and the second being a dictionary of auxiliary operators.
- Tipo del valor devuelto:
tuple[qiskit_nature.second_q.operators.sparse_label_op.SparseLabelOp, dict[str, qiskit_nature.second_q.operators.sparse_label_op.SparseLabelOp]]