MOPS: Multivariate Orthogonal Polynomials (symbolically)

dc.creatorDumitriu, Ioana
dc.creatorEdelman, Alan
dc.creatorShuman, Gene
dc.date2004-09-24
dc.date.accessioned2026-07-07T04:31:29Z
dc.date.available2026-07-07T04:31:29Z
dc.descriptionIn this paper we present a Maple library (MOPs) for computing Jack, Hermite, Laguerre, and Jacobi multivariate polynomials, as well as eigenvalue statistics for the Hermite, Laguerre, and Jacobi ensembles of Random Matrix theory. We also compute multivariate hypergeometric functions, and offer both symbolic and numerical evaluations for all these quantities. We prove that all algorithms are well-defined, analyze their complexity, and illustrate their performance in practice. Finally, we also present a few of the possible applications of this library.
dc.description42 pages, 5 figures
dc.identifierhttps://arxiv.org/abs/math-ph/0409066
dc.identifierhttp://arxiv.org/abs/math-ph/0409066
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/57830
dc.subjectMathematical Physics
dc.subject15A52, 46N99
dc.titleMOPS: Multivariate Orthogonal Polynomials (symbolically)
dc.typetext

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