Applications of multiple orthogonal polynomials with hypergeometric moment generating functions

IF 1 3区 数学 Q3 MATHEMATICS, APPLIED
Thomas Wolfs
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引用次数: 0

Abstract

We investigate several families of multiple orthogonal polynomials associated with weights for which the moment generating functions are hypergeometric series with slightly varying parameters. The weights are supported on the unit interval, the positive real line, or the unit circle and the multiple orthogonal polynomials are generalizations of the Jacobi, Laguerre or Bessel orthogonal polynomials. We give explicit formulas for the type I and type II multiple orthogonal polynomials and study some of their properties. In particular, we describe the asymptotic distribution of the (scaled) zeros of the type II multiple orthogonal polynomials via the free convolution. Essential to our overall approach is the use of the Mellin transform. Finally, we discuss two applications. First, we show that the multiple orthogonal polynomials appear naturally in the study of the squared singular values of (mixed) products of truncated unitary random matrices and Ginibre matrices. Secondly, we use the multiple orthogonal polynomials to simultaneously approximate certain hypergeometric series and to provide an explicit proof of their Q-linear independence.

具有超几何矩生成函数的多重正交多项式的应用
我们研究了多个与权重相关的多重正交多项式族,这些权重的矩生成函数是参数略有变化的超几何级数。权重支持单位区间、正实线或单位圆,多重正交多项式是雅可比、拉盖尔或贝塞尔正交多项式的广义化。我们给出了 I 型和 II 型多重正交多项式的明确公式,并研究了它们的一些性质。特别是,我们通过自由卷积描述了 II 型多重正交多项式(缩放)零点的渐近分布。梅林变换的使用对我们的整体方法至关重要。最后,我们讨论两个应用。首先,我们展示了多重正交多项式自然出现在截断单元随机矩阵和吉尼布雷矩阵的(混合)乘积的平方奇异值研究中。其次,我们利用多重正交多项式同时逼近某些超几何级数,并明确证明了它们的 Q 线性独立性。
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来源期刊
Advances in Applied Mathematics
Advances in Applied Mathematics 数学-应用数学
CiteScore
2.00
自引率
9.10%
发文量
88
审稿时长
85 days
期刊介绍: Interdisciplinary in its coverage, Advances in Applied Mathematics is dedicated to the publication of original and survey articles on rigorous methods and results in applied mathematics. The journal features articles on discrete mathematics, discrete probability theory, theoretical statistics, mathematical biology and bioinformatics, applied commutative algebra and algebraic geometry, convexity theory, experimental mathematics, theoretical computer science, and other areas. Emphasizing papers that represent a substantial mathematical advance in their field, the journal is an excellent source of current information for mathematicians, computer scientists, applied mathematicians, physicists, statisticians, and biologists. Over the past ten years, Advances in Applied Mathematics has published research papers written by many of the foremost mathematicians of our time.
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