将随机矩阵映射枚举与贝塞尔-阿佩尔多项式递归算子的通用符号演算联系起来

IF 0.9 4区 数学 Q4 PHYSICS, MATHEMATICAL
N. Ercolani, Patrick Waters
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引用次数: 0

摘要

地图是黎曼曲面上的多边形细胞网络。本文分析了与固定但任意属映射相关的枚举生成函数的封闭形式一般表示的构造。本文提出的构造方法基于厄米随机矩阵的谱渐近性与指数权重正交多项式的渐近性之间的关系,涉及差分算子的一种新的渐近符号演算。这些封闭形式表达式在某种意义上具有普遍的特征,即它们独立于一个广泛类别内的细胞网络的显式价分布。然而,价态分布可以通过贝塞尔函数生成的阿佩尔多项式的显着展开恒等式从闭合形式生成函数中恢复。我们的处理揭示了生成函数是非线性守恒律及其延伸的解。这种特性使人们能够获得超越纯粹组合的传统方法的见解。通俗性结果与Caflisch, Ercolani, Hou和Landis研究的守恒律特征奇异性的稳定性结果相联系,非线性双曲型或椭圆型系统的多值解和分支点奇异性,共。纯粹的达成。数学46(1993)453-499,以及与随机矩阵谱的普适性结果直接相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Relating random matrix map enumeration to a universal symbol calculus for recurrence operators in terms of Bessel–Appell polynomials
Maps are polygonal cellular networks on Riemann surfaces. This paper analyzes the construction of closed form general representations for the enumerative generating functions associated to maps of fixed but arbitrary genus. The method of construction developed here involves a novel asymptotic symbol calculus for difference operators based on the relation between spectral asymptotics for Hermitian random matrices and asymptotics of orthogonal polynomials with exponential weights. These closed form expressions have a universal character in the sense that they are independent of the explicit valence distribution of the cellular networks within a broad class. Nevertheless the valence distributions may be recovered from the closed form generating functions by a remarkable unwinding identity in terms of Appell polynomials generated by Bessel functions. Our treatment reveals the generating functions to be solutions of nonlinear conservation laws and their prolongations. This characterization enables one to gain insights that go beyond more traditional methods that are purely combinatorial. Universality results are connected to stability results for characteristic singularities of conservation laws that were studied by Caflisch, Ercolani, Hou and Landis, Multi-valued solutions and branch point singularities for nonlinear hyperbolic or elliptic systems, Commun. Pure Appl. Math. 46 (1993) 453–499, as well as directly related to universality results for random matrix spectra.
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来源期刊
Random Matrices-Theory and Applications
Random Matrices-Theory and Applications Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.90
自引率
11.10%
发文量
29
期刊介绍: Random Matrix Theory (RMT) has a long and rich history and has, especially in recent years, shown to have important applications in many diverse areas of mathematics, science, and engineering. The scope of RMT and its applications include the areas of classical analysis, probability theory, statistical analysis of big data, as well as connections to graph theory, number theory, representation theory, and many areas of mathematical physics. Applications of Random Matrix Theory continue to present themselves and new applications are welcome in this journal. Some examples are orthogonal polynomial theory, free probability, integrable systems, growth models, wireless communications, signal processing, numerical computing, complex networks, economics, statistical mechanics, and quantum theory. Special issues devoted to single topic of current interest will also be considered and published in this journal.
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