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AuthorHashemi, Behnam
AuthorNakatsukasa, Yuji
AuthorTrefethen, Lloyd N.
Available date2022-12-27T05:43:23Z
Publication Date2022-12-01
Publication NameAdvances in Computational Mathematics
Identifierhttp://dx.doi.org/10.1007/s10444-022-09994-8
CitationHashemi, B., Nakatsukasa, Y. & Trefethen, L.N. Rectangular eigenvalue problems. Adv Comput Math 48, 80 (2022). https://doi.org/10.1007/s10444-022-09994-8
ISSN10197168
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85142090561&origin=inward
URIhttp://hdl.handle.net/10576/37609
AbstractOften the easiest way to discretize an ordinary or partial differential equation is by a rectangular numerical method, in which n basis functions are sampled at m ≫ n collocation points. We show how eigenvalue problems can be solved in this setting by QR reduction to square matrix generalized eigenvalue problems. The method applies equally in the limit “m= ∞” of eigenvalue problems for quasimatrices. Numerical examples are presented as well as pointers to related literature.
Languageen
PublisherSpringer
SubjectEigenvalue problems
Fourier extension
Helmholtz equation
Lightning solver
Method of fundamental solutions
Quasimatrix
Spectral methods
Vandermonde with Arnoldi
TitleRectangular eigenvalue problems
TypeArticle
Issue Number6
Volume Number48
ESSN1572-9044
dc.accessType Open Access


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