SearchSpaceFactorΒΆ

Type:float
Range:[1, inf]
Default:1.0
Appearance:simple

In a nutshell, an eigensolver approximate eigenvectors by a weighted sum over basis vectors of a lower-dimensional subspace (search space). At least the search space has a dimension of the number of sought eigenvectors (SearchSpaceFactor=1), but the larger the search space the faster is the convergence. This parameter increases the search space dimension (\mathrm{dim}_{\mathrm{s}}) as follows:

\begin{eqnarray*}
\mathrm{dim}_{\mathrm{s}} = (f_0+f) \mathrm{N}_{\mathrm{ev}},
\end{eqnarray*}

where f_0 is an implementation dependent offset factor, f is the user defined SearchSpaceFactor, \mathrm{N}_{\mathrm{ev}} is the number of desired eigenvalues.