Random Matrices, Volume 142, Third Edition (Pure and Applied Mathematics) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


Random Matrices, Volume 142, Third Edition (Pure and Applied Mathematics)

简体网页||繁体网页
Madan Lal Mehta 作者
Academic Press
译者
2004-11-02 出版日期
706 页数
USD 107.00 价格
Hardcover
丛书系列
9780120884094 图书编码

Random Matrices, Volume 142, Third Edition (Pure and Applied Mathematics) 在线电子书 图书标签: 物理  Probability  Math   


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Random Matrices, Volume 142, Third Edition (Pure and Applied Mathematics) 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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Random Matrices, Volume 142, Third Edition (Pure and Applied Mathematics) 在线电子书 图书描述

This book gives a coherent and detailed description of analytical methods devised to study random matrices. These methods are critical to the understanding of various fields in in mathematics and mathematical physics, such as nuclear excitations, ultrasonic resonances of structural materials, chaotic systems, the zeros of the Riemann and other zeta functions. More generally they apply to the characteristic energies of any sufficiently complicated system and which have found, since the publication of the second edition, many new applications in active research areas such as quantum gravity, traffic and communications networks or stock movement in the financial markets.

This revised and enlarged third edition reflects the latest developements in the field and convey a greater experience with results previously formulated. For example, the theory of skew-orthogoanl and bi-orthogonal polynomials, parallel to that of the widely known and used orthogonal polynomials, is explained here for the first time.

· Presentation of many new results in one place for the first time.

· First time coverage of skew-orthogonal and bi-orthogonal polynomials and their use in the evaluation of some multiple integrals.

· Fredholm determinants and Painlevé equations.

· The three Gaussian ensembles (unitary, orthogonal, and symplectic); their n-point correlations, spacing probabilities.

· Fredholm determinants and inverse scattering theory.

· Probability densities of random determinants.

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