Zeros of Gaussian Analytic Functions and Determinantal Point Processes

J. Hough, Manjunath Krishnapur, Y. Peres, B. Virág
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引用次数: 547

Abstract

The book examines in some depth two important classes of point processes, determinantal processes and 'Gaussian zeros', i.e., zeros of random analytic functions with Gaussian coefficients. These processes share a property of 'point-repulsion', where distinct points are less likely to fall close to each other than in processes, such as the Poisson process, that arise from independent sampling. Nevertheless, the treatment in the book emphasizes the use of independence: for random power series, the independence of coefficients is key; for determinantal processes, the number of points in a domain is a sum of independent indicators, and this yields a satisfying explanation of the central limit theorem (CLT) for this point count. Another unifying theme of the book is invariance of considered point processes under natural transformation groups. The book strives for balance between general theory and concrete examples. On the one hand, it presents a primer on modern techniques on the interface of probability and analysis. On the other hand, a wealth of determinantal processes of intrinsic interest are analyzed; these arise from random spanning trees and eigenvalues of random matrices, as well as from special power series with determinantal zeros. The material in the book formed the basis of a graduate course given at the IAS-Park City Summer School in 2007; the only background knowledge assumed can be acquired in first-year graduate courses in analysis and probability.
高斯解析函数的零点与行列式点过程
本书深入探讨了两类重要的点过程,行列式过程和“高斯零”,即具有高斯系数的随机解析函数的零。这些过程都具有“点排斥”的特性,在这些过程中,不同的点不太可能彼此靠近,而不是像泊松过程那样,由独立采样产生。然而,书中的处理强调独立性的使用:对于随机幂级数,系数的独立性是关键;对于行列式过程,一个域中的点数是独立指标的和,这就对这个点数的中心极限定理(CLT)给出了令人满意的解释。本书的另一个统一主题是自然变换群下考虑的点过程的不变性。这本书力求在一般理论和具体实例之间取得平衡。一方面,介绍了概率与分析相结合的现代技术。另一方面,分析了大量具有内在利益的决定过程;这些来源于随机生成树和随机矩阵的特征值,以及具有行列式零的特殊幂级数。书中的材料构成了2007年IAS-Park City暑期学校研究生课程的基础;假设的唯一背景知识可以在第一年的研究生分析和概率课程中获得。
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