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MOPS: Multivariate orthogonal polynomials (symbolically)

In 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...

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Bibliographic Details
Published in:Journal of symbolic computation 2007-06, Vol.42 (6), p.587-620
Main Authors: Dumitriu, Ioana, Edelman, Alan, Shuman, Gene
Format: Article
Language:English
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Summary:In 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 present a few applications of this library.
ISSN:0747-7171
1095-855X
DOI:10.1016/j.jsc.2007.01.005