
AbstractNon-symmetric and symmetric twisted block factorizations of block tridiagonal matrices are discussed. In contrast to non-blocked factorizations of this type, localized pivoting strategies can be integrated which improves numerical stability without causing any extra fill-in. Moreover, the application of such factorizations for approximating an eigenvector of a block tridiagonal matrix, given an approximation of the corresponding eigenvalue, is outlined. A heuristic strategy for determining a suitable starting vector for the underlying inverse iteration process is proposed.
101014 Numerical mathematics, Block tridiagonal eigenvalue problem, Eigenvector computation, 102023 Supercomputing, Twisted block factorizations, Twisted factorizations, 101014 Numerische Mathematik, /dk/atira/pure/subjectarea/asjc/1700, Computer Science(all)
101014 Numerical mathematics, Block tridiagonal eigenvalue problem, Eigenvector computation, 102023 Supercomputing, Twisted block factorizations, Twisted factorizations, 101014 Numerische Mathematik, /dk/atira/pure/subjectarea/asjc/1700, Computer Science(all)
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