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Exact Schur solve for a full-row-rank symmetric saddle system
Statement
Under the hypotheses of Symmetric saddle-point system, Schur complement, and block preconditioners, is positive definite and hence invertible. For every and , the unique solution of is The factorization used in this solve is the published block-LU factorization An invertible leading block yields block LU through its Schur complement.
Facts & Assumptions
Given: symmetric positive definite, full row rank, and the finite-dimensional symmetric saddle equations with right-hand side .
The saddle matrix, pressure Schur matrix , and the two equations are defined in Symmetric saddle-point system, Schur complement, and block preconditioners.
If a square block matrix has an invertible leading block, it factorizes through the Schur complement as (An invertible leading block yields block LU through its Schur complement).
For a linear map between finite-dimensional spaces, (Rank-nullity: ).
Proof
Positive definiteness of makes its kernel zero: if , then , so the positivity hypothesis forces . Since is a square matrix on a finite-dimensional space, [F3] makes its image full-dimensional; thus is invertible. For nonzero , full row rank gives . Put , which is nonzero. Then Therefore is symmetric positive definite.
Apply [F2] to with leading block , upper-right block , lower-left block , and lower-right block . Its trailing Schur complement is . Hence and both diagonal blocks of the upper factor are invertible by the hypotheses and step 1.1.
Solve the lower-triangular factor against first. It gives the intermediate vector . The second block row of the upper solve is , so . The first row gives . Substitution verifies and . Invertibility of the diagonal blocks in step 2.1 makes both triangular solves unique, so this is the unique solution.
Depends on
Used by
Nothing in the library uses this result yet.
Cited to discharge well-definedness by Symmetric saddle-point system, Schur complement, and block preconditioners.
Dependency tree · two levels
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Sources
- Michele Benzi, Gene H. Golub, and Jörg Liesen, Numerical solution of saddle point problems (standard reference, not scraped)