Log-gases and random matrices

Random matrix theory, both as an application and as a theory, has evolved rapidly over the past fifteen years. Log-Gases and Random Matrices gives a comprehensive account of these developments, emphasizing log-gases as a physical picture and heuristic, as well as covering topics such as beta ensembl...

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Bibliographic Details
Main Author:	Forrester, P.J
Format:	eBook Book
Language:	English
Published:	Princeton Princeton University Press 2010
Edition:	1
Series:	London Mathematical Society Monographs
Subjects:	Asymptotic formula Bidiagonal matrix Binomial coefficient Calculation Central limit theorem Change of variables Characteristic polynomial Coefficient Correlation function Correlation function (quantum field theory) Cumulative distribution function Determinant Diagram (category theory) Differential equation Dirac equation Dirac operator Eigenfunction Eigenvalues and eigenvectors Elliptic function Equation Euler's formula Explicit formulae (L-function) Factorization Fredholm determinant Gamma function Geometric distribution Haar measure Hecke algebra Hermite polynomials Hermitian matrix Hessenberg matrix Integer matrix Integral equation Integral theorems Jacobi polynomials Joint probability distribution Laplace's equation Lattice path MATHEMATICS MATHEMATICS / Matrices MATHEMATICS / Probability & Statistics / General Nucleation Operator (physics) Orthogonal polynomials Partial differential equation Partial fraction decomposition Partition function (mathematics) Partition function (statistical mechanics) Permutation Permutation matrix Pfaffian Poisson point process Polynomial Power series Probability Probability density function Probability measure Quaternion Random matrices Random matrix Riemann sum Riemann zeta function Scaling limit Scatter matrix Schur polynomial Statistic Statistical mechanics Statistics Subsequence Symmetric matrix Symmetrization Symplectic matrix Trace formula Tridiagonal matrix Unitary matrix Volume form Polynomial Random matrix Nucleation Eigenfunction Pfaffian Trace formula Hermitian matrix Laplace's equation Lattice path Gamma function Partial differential equation Cumulative distribution function Euler's formula Eigenvalues and eigenvectors Probability density function Correlation function Calculation Integral equation Symplectic matrix Explicit formulae (L-function) Jacobi polynomials Bidiagonal matrix Volume form Permutation Determinant Elliptic function Geometric distribution Fredholm determinant Poisson point process Haar measure Partition function (mathematics) Partial fraction decomposition Partition function (statistical mechanics) Subsequence Hessenberg matrix Joint probability distribution Statistical mechanics Tridiagonal matrix Riemann sum Probability measure Symmetrization Quaternion Differential equation Scaling limit Change of variables Characteristic polynomial Operator (physics) Diagram (category theory) Schur polynomial Power series Asymptotic formula Hecke algebra Statistic Orthogonal polynomials Riemann zeta function Binomial coefficient Hermite polynomials Dirac operator Unitary matrix Coefficient Scatter matrix Probability Equation Factorization Integer matrix Correlation function (quantum field theory) Permutation matrix Central limit theorem Symmetric matrix Dirac equation
ISBN:	9781400835416, 1400835410, 9780691128290, 0691128294
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Summary:	Random matrix theory, both as an application and as a theory, has evolved rapidly over the past fifteen years. Log-Gases and Random Matrices gives a comprehensive account of these developments, emphasizing log-gases as a physical picture and heuristic, as well as covering topics such as beta ensembles and Jack polynomials.
Bibliography:	Includes bibliographical references (p. [765]-784) and index
ISBN:	9781400835416 1400835410 9780691128290 0691128294
DOI:	10.1515/9781400835416