random walks
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1: 16.24 Physical Applications
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§16.24(i) Random Walks
►Generalized hypergeometric functions and Appell functions appear in the evaluation of the so-called Watson integrals which characterize the simplest possible lattice walks. They are also potentially useful for the solution of more complicated restricted lattice walk problems, and the 3D Ising model; see Barber and Ninham (1970, pp. 147–148). …2: Bibliography B
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On the distribution of the length of the longest increasing subsequence of random permutations.
J. Amer. Math. Soc. 12 (4), pp. 1119–1178.
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Random and Restricted Walks: Theory and Applications.
Gordon and Breach, New York.
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Focusing and twinkling: Critical exponents from catastrophes in non-Gaussian random short waves.
J. Phys. A 10 (12), pp. 2061–2081.
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3: 16.23 Mathematical Applications
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§16.23(ii) Random Graphs
►A substantial transition occurs in a random graph of vertices when the number of edges becomes approximately . …4: 35.9 Applications
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►In multivariate statistical analysis based on the multivariate normal distribution, the probability density functions of many random matrices are expressible in terms of generalized hypergeometric functions of matrix argument , with and .
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►In the nascent area of applications of zonal polynomials to the limiting probability distributions of symmetric random matrices, one of the most comprehensive accounts is Rains (1998).
5: 32.14 Combinatorics
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►The distribution function given by (32.14.2) arises in random matrix theory where it gives the limiting distribution for the normalized largest eigenvalue in the Gaussian Unitary Ensemble of Hermitian matrices; see Tracy and Widom (1994).
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►See Forrester and Witte (2001, 2002) for other instances of Painlevé equations in random matrix theory.
6: 27.19 Methods of Computation: Factorization
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►Type II probabilistic algorithms for factoring rely on finding a pseudo-random pair of integers that satisfy .
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7: 18.38 Mathematical Applications
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Random Matrix Theory
►Hermite polynomials (and their Freud-weight analogs (§18.32)) play an important role in random matrix theory. …8: Bibliography F
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Application of the -function theory of Painlevé equations to random matrices: PIV, PII and the GUE.
Comm. Math. Phys. 219 (2), pp. 357–398.
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Application of the -function theory of Painlevé equations to random matrices: , , the LUE, JUE, and CUE.
Comm. Pure Appl. Math. 55 (6), pp. 679–727.
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Application of the -function theory of Painlevé equations to random matrices: , the JUE, CyUE, cJUE and scaled limits.
Nagoya Math. J. 174, pp. 29–114.
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Introduction to the Random Matrix Theory: Gaussian Unitary Ensemble and Beyond.
In Recent Perspectives in Random Matrix Theory and Number Theory,
London Math. Soc. Lecture Note Ser., Vol. 322, pp. 31–78.
9: Bibliography I
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Statistical Field Theory: Strong Coupling, Monte Carlo Methods, Conformal Field Theory, and Random Systems.
Vol. 2, Cambridge University Press, Cambridge.
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10: Bibliography D
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Orthogonal Polynomials and Random Matrices: A Riemann-Hilbert Approach.
Courant Lecture Notes in Mathematics, Vol. 3, New York University Courant Institute of Mathematical
Sciences, New York.
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Uniform asymptotics for polynomials orthogonal with respect to varying exponential weights and applications to universality questions in random matrix theory.
Comm. Pure Appl. Math. 52 (11), pp. 1335–1425.
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D gravity and random matrices.
Phys. Rep. 254 (1-2), pp. 1–133.
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