Lanczosprocessen
Lanczosprocessen, also known as the Lanczos algorithm, is an iterative numerical method used to find the eigenvalues and eigenvectors of large, sparse, and symmetric or Hermitian matrices. It is particularly effective when only a few eigenvalues, usually those closest to a specific value or at the extremes of the spectrum, are of interest. The algorithm works by constructing a Krylov subspace, which is a sequence of subspaces spanned by successive applications of a matrix to an initial vector.
The core idea of the Lanczos algorithm is to project the large matrix onto a smaller, tridiagonal
Developed by Cornelius Lanczos in the 1950s, the algorithm has found widespread applications in various fields,