def __init__(self, nqubits, matrix):
if not (isinstance(matrix, K.tensor_types) or K.issparse(matrix)):
raise_error(
TypeError, "Matrix of invalid type {} given during "
"Hamiltonian initialization"
"".format(type(matrix)))
self.K = K
matrix = self.K.cast(matrix)
super().__init__(nqubits, matrix)
def __mul__(self, o):
if isinstance(o, K.tensor_types):
o = complex(o)
elif not isinstance(o, K.numeric_types):
raise_error(
NotImplementedError, "Hamiltonian multiplication to {} "
"not implemented.".format(type(o)))
new_matrix = self.matrix * o
r = self.__class__(self.nqubits, new_matrix)
if self._eigenvalues is not None:
if K.qnp.cast(o).real >= 0:
r._eigenvalues = o * self._eigenvalues
elif not K.issparse(self.matrix):
r._eigenvalues = o * self._eigenvalues[::-1]
if self._eigenvectors is not None:
if K.qnp.cast(o).real > 0:
r._eigenvectors = self._eigenvectors
elif o == 0:
r._eigenvectors = self.eye(int(self._eigenvectors.shape[0]))
return r
