Massei S., Palitta D., Robol L.
numerical range algorithms H -matrices quadrature quasiseparable matrices H-matrices Quasiseparable matrices decay bounds Banded matrices Lyapunov equation Sylvester equation Off-diagonal singular values off-diagonal singular values riccati-equations Analysis singular-values matrices banded matrices
We consider the problem of efficiently solving Sylvester and Lyapunov equations of medium and large scale, in case of rank-structured data, i.e., when the coefficient matrices and the right-hand side have low-rank off-diagonal blocks. This comprises problems with banded data, recently studied in [A. Haber and M. Verhaegen, Automatica J. IFAC, 73 (2016), pp. 256-268; D. Palitta and V. Simoncini, Numerical Methods for Large-Scale Lyapunov Equations with Symmetric Banded Data, preprint, arxiv, 1711.04187, 2017], which often arise in the discretization of elliptic PDEs. We show that, under suitable assumptions, the quasiseparable structure is guaranteed to be numerically present in the solution, and explicit novel estimates of the numerical rank of the offdiagonal blocks are provided. Efficient solution schemes that rely on the technology of hierarchical matrices are described, and several numerical experiments confirm the applicability and efficiency of the approaches. We develop a MATLAB toolbox that allows easy replication of the experiments and a ready-to-use interface for the solvers. The performances of the different approaches are compared, and we show that the new methods described are efficient on several classes of relevant problems.
Source: SIAM journal on matrix analysis and applications (Print) 39 (2018): 1564–1590. doi:10.1137/17M1157155
Publisher: Society for Industrial and Applied Mathematics ,, Philadelphia, Pa. , Stati Uniti d'America
@article{oai:it.cnr:prodotti:396727, title = {Solving rank-structured Sylvester and Lyapunov equations}, author = {Massei S. and Palitta D. and Robol L.}, publisher = {Society for Industrial and Applied Mathematics ,, Philadelphia, Pa. , Stati Uniti d'America}, doi = {10.1137/17m1157155}, journal = {SIAM journal on matrix analysis and applications (Print)}, volume = {39}, pages = {1564–1590}, year = {2018} }