Sparse block factorization of saddle point matrices

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The factorization method presented in this paper takes advantage of the special structures and properties of saddle point matrices. A variant of Gaussian elimination equivalent to the Cholesky's factorization is suggested and implemented for factorizing the saddle point matrices block-wise with small blocks of orders 1 and 2. The Gaussian elimination applied to these small blocks on block level also induces a block 3×3 structured factorization of which the blocks have special properties. We compare the new block factorization with the Schilders' factorization in terms of sparsity and computational complexity. The factorization can be used as a direct method, and also anticipate for preconditioning techniques. Keywords: Saddle point matrices; Sparse matrices; Transformation matrix; Block partitioning; Block factorization; Schilders' factorization
Original languageEnglish
Pages (from-to)214–242
Number of pages29
JournalLinear Algebra and Its Applications
Publication statusPublished - 2016


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