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Numerical Solution of Large-Scale Low-Rank Coupled Generalized Sylvester Equations
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arXiv:2610.30804v1 Announce Type: cross Abstract: This paper develops projection methods for computing low-rank solutions to large-scale coupled generalized Sylvester equations. The dominant subspaces of these solutions are shown to be spanned by specific resolvent directions, motivating a Petrov--Galerkin projection framework. Conditions for the unique solvability of the projected coupled generalized Sylvester equations are also discussed. Based on these dominant subspaces, two algorithms are proposed: an extended Krylov-based projection algorithm and a rational Krylov-based projection algorithm. The former uses fixed shifts, whereas the latter uses adaptive shifts. Numerical experiments on large-scale benchmark problems demonstrate that the proposed methods achieve high accuracy and fast convergence.
Source:https://arxiv.org/abs/2610.30804PreviousBehavioral Mapping of Hierarchical Dynamical Models Accelerates Bayesian Parameter InferenceNextPriMa-Causa: Causal Prescriptive Maintenance
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