PDOS

sisl.physics.phonon.PDOS(E, mode, hw, distribution='gaussian')

Calculate the projected density of modes (PDOS) onto each each atom and direction for a set of energies, E, with a distribution function

The $\mathrm{PDOS}(E)$ is calculated as:

$${\mathrm{PDOS}}_{\alpha }(E)=\sum _i{ϵ}_{i,\alpha }^{\ast }{ϵ}_{i,\alpha }D(E-\hslash {\omega }_i)$$

where $D(\mathrm{\Delta }E)$ is the distribution function used. Note that the distribution function used may be a user-defined function. Alternatively a distribution function may be aquired from distribution.

$$\mathrm{DOS}(E)=\sum _{\alpha }{\mathrm{PDOS}}_{\alpha }(E)$$

Parameters:

• E (ndarray) – energies to calculate the projected-DOS from

• mode (ndarray) – eigenvectors

• hw (ndarray) – eigenvalues

• distribution (Literal['gaussian', 'lorentzian', 'fermi', 'bose-einstein', 'cold', 'step-function', 'heaviside'] | ~typing.Callable[[~collections.abc.Buffer | ~numpy._typing._array_like._SupportsArray[~numpy.dtype[~typing.Any]] | ~numpy._typing._nested_sequence._NestedSequence[~numpy._typing._array_like._SupportsArray[~numpy.dtype[~typing.Any]]] | bool | int | float | complex | str | bytes | ~numpy._typing._nested_sequence._NestedSequence[bool | int | float | complex | str | bytes]], ~numpy.ndarray]) – a function that accepts $E-ϵ$ as argument and calculates the distribution function.

See also

Distribution functions

a selected set of implemented distribution functions

DOS

total DOS (same as summing over atoms and directions)

Returns:

projected DOS calculated at energies, has dimension (mode.shape[1], len(E)).

Return type:

numpy.ndarray

Parameters:

distribution (Literal['gaussian', 'lorentzian', 'fermi', 'bose-einstein', 'cold', 'step-function', 'heaviside'] | ~typing.Callable[[~collections.abc.Buffer | ~numpy._typing._array_like._SupportsArray[~numpy.dtype[~typing.Any]] | ~numpy._typing._nested_sequence._NestedSequence[~numpy._typing._array_like._SupportsArray[~numpy.dtype[~typing.Any]]] | bool | int | float | complex | str | bytes | ~numpy._typing._nested_sequence._NestedSequence[bool | int | float | complex | str | bytes]], ~numpy.ndarray])