MOPS: Multivariate Orthogonal Polynomials (symbolically)
Mathematical Physics
2007-05-23 v1 math.MP
Abstract
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 also present a few of the possible applications of this library.
Cite
@article{arxiv.math-ph/0409066,
title = {MOPS: Multivariate Orthogonal Polynomials (symbolically)},
author = {Ioana Dumitriu and Alan Edelman and Gene Shuman},
journal= {arXiv preprint arXiv:math-ph/0409066},
year = {2007}
}
Comments
42 pages, 5 figures