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The GSO Hamiltonian is characterized by having no distinct structure
Inherits From: Hamiltonian
fqe.gso_hamiltonian.GSOHamiltonian(
tensors: Tuple[np.ndarray, ...],
e_0: complex = (0.0 + 0.0j)
) -> None
in the elements beyond being hermitian. An example is a relativistic molecular Hamiltonian.
Arguments | |
|---|---|
tensors
|
Variable length tuple containg between one and four numpy.arrays of increasing rank. The tensors contain the n-body hamiltonian elements. Tensors up to the highest order must be included even if the lower terms are full of zeros. |
e_0
|
Scalar potential associated with the Hamiltonian. |
Methods
calc_diag_transform
calc_diag_transform() -> np.ndarray
Performs a unitary digaonlizing transformation of the one body term and returns that transformation.
conserve_number
conserve_number() -> bool
Returns True if the Hamiltonian is number conserving, else False.
diag_values
diag_values() -> np.ndarray
Returns the diagonal values packed into a single dimension.
diagonal
diagonal() -> bool
Returns True if the Hamiltonian is diagonal, else False.
diagonal_coulomb
diagonal_coulomb() -> bool
Returns True if the Hamiltonian is diagonal coloumb, else False.
dim
dim() -> int
Returns the orbital dimension of the Hamiltonian arrays.
e_0
e_0()
Returns the scalar potential of the Hamiltonian.
iht
iht(
time: float
) -> Tuple[np.ndarray, ...]
Returns the matrices of the Hamiltonian prepared for time evolution.
quadratic
quadratic() -> bool
Returns whether or not the Hamiltonian is quadratic.
rank
rank() -> int
This returns the rank of the largest tensor.
tensor
tensor(
rank: int
) -> np.ndarray
Returns a single nbody tensor based on its rank.
| Args | |
|---|---|
rank
|
Indexes the single nbody tensor to return. |
tensors
tensors() -> Tuple[np.ndarray, ...]
Returns all tensors in order of their rank.
transform
transform(
trans: np.ndarray
) -> np.ndarray
Tranforms the one body term using the provided matrix.
| Args | |
|---|---|
trans
|
Unitary transformation. |
| Returns | |
|---|---|
| Transformed one-body Hamiltonian as a numpy.ndarray. |