A note on $2\times 2$ block-diagonal preconditioning
Ben S. Southworth, Samuel A. Olivier

TL;DR
This paper investigates the convergence properties of block-diagonal preconditioning for 2x2 block matrices, revealing limitations and comparing its performance to other preconditioners in practical applications.
Contribution
It proves that minimal-residual methods with block-diagonal preconditioning do not always converge quickly and compares their effectiveness to block-triangular preconditioning in various scenarios.
Findings
Block-diagonal preconditioning may not converge in a fixed number of iterations.
Examples show equivalence in convergence speed between certain preconditioners.
Practical applications demonstrate scenarios where block-diagonal preconditioning is advantageous.
Abstract
For 2x2 block matrices, it is well-known that block-triangular or block-LDU preconditioners with an exact Schur complement (inverse) converge in at most two iterations for fixed-point or minimal-residual methods. Similarly, for saddle-point matrices with a zero (2,2)-block, block-diagonal preconditioners converge in at most three iterations for minimal-residual methods, although they may diverge for fixed-point iterations. But, what happens for non-saddle-point matrices and block-diagonal preconditioners with an exact Schur complement? This note proves that minimal-residual methods applied to general 2x2 block matrices, preconditioned with a block-diagonal preconditioner, including an exact Schur complement, do not (necessarily) converge in a fixed number of iterations. Furthermore, examples are constructed where (i) block-diagonal preconditioning with an exact Schur complement…
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Taxonomy
TopicsMatrix Theory and Algorithms · Electromagnetic Scattering and Analysis · Advanced Numerical Methods in Computational Mathematics
