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The probability that an interval $I$ is free of eigenvalues in a matrix ensemble with unitary symmetry is given by a Fredholm determinant. When the weight function in the matrix ensemble is a classical weight function, and the interval $I$…

Mathematical Physics · Physics 2007-05-23 N. S. Witte , P. J. Forrester , Christopher M. Cosgrove

We consider a discrete polynuclear growth (PNG) process and prove a functioal limit theorem for its convergrence to the Airy process. This generalizes previous results by Pr"ahofer and Spohn. The result enables us to express the GOE largest…

Probability · Mathematics 2009-11-07 Kurt Johansson

We study the one parameter family of Fredholm determinants $\det(I-\gamma K_{\textnormal{csin}}),\gamma\in\mathbb{R}$ of an integrable Fredholm operator $K_{\textnormal{csin}}$ acting on the interval $(-s,s)$ whose kernel is a cubic…

Exactly Solvable and Integrable Systems · Physics 2013-03-11 Thomas Bothner , Alexander Its

We call "Dyson process" any process on ensembles of matrices in which the entries undergo diffusion. We are interested in the distribution of the eigenvalues (or singular values) of such matrices. In the original Dyson process it was the…

Probability · Mathematics 2007-05-23 Craig A. Tracy , Harold Widom

We show that the ratio of a discrete Toeplitz/Hankel determinant and its continuous counterpart equals a Freholm determinant involving continuous orthogonal polynomials. This identity is used to evaluate a triple asymptotic of some discrete…

Probability · Mathematics 2013-05-20 Jinho Baik , Zhipeng Liu

We show that near a point where the equilibrium density of eigenvalues of a matrix model behaves like y ~ x^{p/q}, the correlation functions of a random matrix, are, to leading order in the appropriate scaling, given by determinants of the…

Mathematical Physics · Physics 2009-09-08 Michel Bergere , Bertrand Eynard

We present the conditional determinantal point process (DPP) approach to obtain new (mostly Fredholm determinantal) expressions for various eigenvalue statistics in random matrix theory. It is well-known that many (especially $\beta=2$)…

Mathematical Physics · Physics 2023-10-23 Alan Edelman , Sungwoo Jeong

This paper introduces a novel approach to probabilistic deep learning, kernel density matrices, which provide a simpler yet effective mechanism for representing joint probability distributions of both continuous and discrete random…

Machine Learning · Computer Science 2024-05-01 Fabio A. González , Raúl Ramos-Pollán , Joseph A. Gallego-Mejia

We consider discrete orthogonal polynomial ensembles which are discrete analogues of the orthogonal polynomial ensembles in random matrix theory. These ensembles occur in certain problems in combinatorial probability and can be thought of…

Combinatorics · Mathematics 2007-05-23 Kurt Johansson

Noncolliding Brownian motion (Dyson's Brownian motion model with parameter $\beta=2$) and noncolliding Bessel processes are determinantal processes; that is, their space-time correlation functions are represented by determinants. Under a…

Probability · Mathematics 2015-02-13 Hirofumi Osada , Hideki Tanemura

The usual formulas for the correlation functions in orthogonal and symplectic matrix models express them as quaternion determinants. From this representation one can deduce formulas for spacing probabilities in terms of Fredholm…

solv-int · Physics 2009-07-11 Craig A. Tracy , Harold Widom

Let $(-A,B,C)$ be a linear system in continuous time $t>0$ with input and output space ${\mathbb C}$ and state space $H$. The scattering (or impulse response) functions $\phi_{(x)}(t)=Ce^{-(t+2x)A}B$ determines a Hankel integral operator…

Analysis of PDEs · Mathematics 2025-12-18 Gordon Blower , Simon J. Malham

Fredholm integral operators that commute with the Hamiltonians of certain quantum mechanical problems with quartic potentials are introduced. The operators are expressed in terms of an Airy function, and their eigenvalues fall off…

High Energy Physics - Theory · Physics 2026-03-13 Ori J. Ganor

We analyze a numerical method for computing Fredholm determinants of trace class and Hilbert Schmidt integral operators defined in terms of matrix-valued kernels on the entire real line. With this method, the Fredholm determinant is…

Numerical Analysis · Mathematics 2025-07-31 Erika Gallo , John Zweck , Yuri Latushkin

Tracy and Widom showed that fundamentally important kernels in random matrix theory arise from differential equations with rational coefficients. More generally, this paper considers symmetric Hamiltonian systems abd determines the…

Functional Analysis · Mathematics 2024-09-24 Gordon Blower

We consider the joint distributions of particle positions for the continuous time totally asymmetric simple exclusion process (TASEP). They are expressed as Fredholm determinants with a kernel defining a signed determinantal point process.…

Mathematical Physics · Physics 2008-01-20 Alexei Borodin , Patrik L. Ferrari , Michael Prähofer , Tomohiro Sasamoto

We represent an algorithm allowing one to construct new classes of partially integrable multidimensional nonlinear partial differential equations (PDEs) starting with the special type of solutions to the (1+1)-dimensional hierarchy of…

Exactly Solvable and Integrable Systems · Physics 2015-05-13 A. I. Zenchuk

Yor's generalized meander is a temporally inhomogeneous modification of the $2(\nu+1)$-dimensional Bessel process with $\nu > -1$, in which the inhomogeneity is indexed by $\kappa \in [0, 2(\nu+1))$. We introduce the non-colliding particle…

Probability · Mathematics 2007-05-23 Makoto Katori , Hideki Tanemura

We consider the symmetric gap probability distributions of certain Freud unitary ensembles. This problem is related to the Hankel determinants generated by the Freud weights supported on the complement of a symmetric interval. By using Chen…

Exactly Solvable and Integrable Systems · Physics 2025-01-17 Chao Min , Liwei Wang

We show that the Riemannian Gaussian distributions on symmetric spaces, introduced in recent years, are of standard random matrix type. We exploit this to compute analytically marginals of the probability density functions. This can be done…

Mathematical Physics · Physics 2021-10-29 Leonardo Santilli , Miguel Tierz
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