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dc.date.accessioned2023-02-06T17:42:21Z
dc.date.available2023-02-06T17:42:21Z
dc.date.created2022-08-31T10:07:03Z
dc.date.issued2023
dc.identifier.citationMortensen, Mikael . A generic and strictly banded spectral Petrov-Galerkin method for differential equations with polynomial coefficients. SIAM Journal on Scientific Computing. 2022
dc.identifier.urihttp://hdl.handle.net/10852/99687
dc.description.abstractIn this paper we describe a generic spectral Petrov–Galerkin method that is sparse and strictly banded for any linear ordinary differential equation with polynomial coefficients. The method applies to all subdivisions of Jacobi polynomials (e.g., Chebyshev and Legendre), utilizes well-known recurrence relations of orthogonal polynomials, and leads to almost exactly the same discretized system of equations as the integration preconditioners [E. A. Coutsias, T. Hagstrom, and D. Torres, Math. Comp., 65 (1996), pp. 611–635] if this method was redesigned to make use of trial functions that satisfy a given problem’s boundary conditions. A link between the new Petrov–Galerkin method and IP is revealed through a new recursion relation for Jacobi polynomials. Because of the strictly banded nature of all coefficient matrices, the new method extends easily and efficiently to multiple dimensions though the use of tensor product methods.
dc.languageEN
dc.titleA generic and strictly banded spectral Petrov-Galerkin method for differential equations with polynomial coefficients
dc.title.alternativeENEngelskEnglishA generic and strictly banded spectral Petrov-Galerkin method for differential equations with polynomial coefficients
dc.typeJournal article
dc.creator.authorMortensen, Mikael
cristin.unitcode185,15,13,15
cristin.unitnameMekanikk
cristin.ispublishedfalse
cristin.fulltextpostprint
cristin.qualitycode2
dc.identifier.cristin2047451
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=SIAM Journal on Scientific Computing&rft.volume=&rft.spage=&rft.date=2022
dc.identifier.jtitleSIAM Journal on Scientific Computing
dc.identifier.volume45
dc.identifier.issue1
dc.identifier.doihttps://doi.org/10.1137/22M1492842
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn1064-8275
dc.type.versionAcceptedVersion


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