因式分解行列式及其在数论中的应用

IF 0.9 4区 数学 Q4 PHYSICS, MATHEMATICAL Random Matrices-Theory and Applications Pub Date : 2024-05-27 DOI:10.1142/s2010326324500102
Estelle Basor, Brian Conrey
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引用次数: 0

摘要

在经典紧凑群上平均的移位特征多项式的乘积以及这些乘积的比率对数理论家来说非常有趣,因为它们模拟了与紧凑群具有相同对称类型的族中 L 函数的类似平均。我们利用托普利兹和托普利兹加汉克尔算子,以及鲍罗丁-奥孔科夫-凯斯-杰罗尼莫和巴索尔-艾哈特的等价性,证明在某些情况下,这些单元平均数会以多项式的形式因子化为交映组和正交组上的平均数。在这些特性的基础上,我们提出了这些平均数精确公式的新证明,其中的 "交换 "项是数论平均数的特征,来自适当汉克尔算子行列式的弗雷德霍姆展开。这是对移位特征多项式乘积之比平均数公式的第四次不同证明;其他证明基于超对称性、对称函数理论和随机矩阵理论中的正交多项式方法。
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Factoring determinants and applications to number theory

Products of shifted characteristic polynomials, and ratios of such products, averaged over the classical compact groups are of great interest to number theorists as they model similar averages of L-functions in families with the same symmetry type as the compact group. We use Toeplitz and Toeplitz plus Hankel operators and the identities of Borodin–Okounkov–Case–Geronimo, and Basor–Ehrhardt to prove that, in certain cases, these unitary averages factor as polynomials into averages over the symplectic group and the orthogonal group. Building on these identities we present new proofs of the exact formulas for these averages where the “swap” terms that are characteristic of the number theoretic averages occur from the Fredholm expansions of the determinants of the appropriate Hankel operator. This is the fourth different proof of the formula for the averages of ratios of products of shifted characteristic polynomials; the other proofs are based on supersymmetry; symmetric function theory, and orthogonal polynomial methods from random matrix theory.

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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.
期刊最新文献
Factoring determinants and applications to number theory Dynamics of a rank-one multiplicative perturbation of a unitary matrix Monotonicity of the logarithmic energy for random matrices Eigenvalue distributions of high-dimensional matrix processes driven by fractional Brownian motion Characteristic polynomials of orthogonal and symplectic random matrices, Jacobi ensembles & L-functions
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