RecursiveSI

class sisl.physics.RecursiveSI(spgeom, infinite, eta=1e-06, bloch=None)

Self-energy object using the Lopez-Sancho Lopez-Sancho algorithm

Methods

__init__(spgeom, infinite[, eta, bloch])	Create a SelfEnergy object from any SparseGeometry
self_energy(E[, k, eta, dtype, eps, bulk])	Return a dense matrix with the self-energy at energy E and k-point k (default Gamma).

self_energy(E, k=None, eta=None, dtype=None, eps=1e-14, bulk=False)

Return a dense matrix with the self-energy at energy E and k-point k (default Gamma).

Parameters:

E : float

energy at which the calculation will take place (should not be complex)

k : array_like, optional

k-point at which the self-energy should be evaluated. the k-point should be in units of the reciprocal lattice vectors, and the semi-infinite component will be automatically set to zero.

eta : float, optional

the imaginary value to evaluate the self-energy with. Defaults to the value with which the object was created

dtype : numpy.dtype

the resulting data type

eps : float, optional

convergence criteria for the recursion

bulk : bool, optional

if true, \(E\cdot \mathbf S - \mathbf H -\boldsymbol\Sigma\) is returned, else \(\boldsymbol\Sigma\) is returned (default).