Global and local scaling limits for the β = 2 Stieltjes–Wigert random matrix ensemble

IF 0.9 4区 数学 Q4 PHYSICS, MATHEMATICAL
P. Forrester
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引用次数: 13

Abstract

The eigenvalue probability density function (PDF) for the Gaussian unitary ensemble has a well-known analogy with the Boltzmann factor for a classical log-gas with pair potential [Formula: see text], confined by a one-body harmonic potential. A generalization is to replace the pair potential by [Formula: see text]. The resulting PDF first appeared in the statistical physics literature in relation to non-intersecting Brownian walkers, equally spaced at time [Formula: see text], and subsequently in the study of quantum many-body systems of the Calogero–Sutherland type, and also in Chern–Simons field theory. It is an example of a determinantal point process with correlation kernel based on the Stieltjes–Wigert polynomials. We take up the problem of determining the moments of this ensemble, and find an exact expression in terms of a particular little [Formula: see text]-Jacobi polynomial. From their large [Formula: see text] form, the global density can be computed. Previous work has evaluated the edge scaling limit of the correlation kernel in terms of the Ramanujan ([Formula: see text]-Airy) function. We show how in a particular [Formula: see text] scaling limit, this reduces to the Airy kernel.
β = 2 stieltje - wigert随机矩阵系综的全局和局部尺度极限
高斯酉系综的本征值概率密度函数(PDF)与具有对势的经典对数气体的玻尔兹曼因子有一个众所周知的相似之处[公式:见文本],受单一谐势的限制。一种推广方法是用[公式:见文本]代替对势。由此产生的PDF首先出现在统计物理文献中,与非相交的布朗行体有关,在时间上等间隔[公式:见文本],随后出现在Calogero-Sutherland类型的量子多体系统研究中,也出现在chen - simons场论中。这是一个基于stieltje - wigert多项式的具有相关核的行列式点过程的例子。我们考虑确定这个集合的矩的问题,并找到一个特定的小的[公式:见文本]-雅可比多项式的精确表达式。从它们的大[公式:见文本]形式,可以计算出全局密度。以前的工作已经根据Ramanujan([公式:见文本]-Airy)函数评估了相关核的边缘缩放极限。我们展示了如何在一个特定的[公式:见文本]缩放限制下,这减少到艾里核。
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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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