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We consider matrix-valued processes described as solutions to stochastic differential equations of very general form. We study the family of the empirical measure-valued processes constructed from the corresponding eigenvalues. We show that…

Probability · Mathematics 2019-01-10 Jacek Małecki , José Luis Pérez

We introduce the concept of Randomly Modulated Gaussian Processes as a unifying framework for modeling, analyzing and classifying anomalous diffusion models in heterogeneous media. This formulation incorporates correlations in the…

Biological Physics · Physics 2026-03-16 Yann Lanoiselée , Denis S. Grebenkov , Gianni Pagnini

We study here the random diffusion model. This is a continuum model for a conserved scalar density field $\phi$ driven by diffusive dynamics. The interesting feature of the dynamics is that the {\it bare} diffusion coefficient $D$ is…

Soft Condensed Matter · Physics 2009-11-13 Gene F. Mazenko

We develop a theory of multilevel distributions of eigenvalues which complements the Dyson's threefold $\beta=1,2,4$ approach corresponding to real/complex/quaternion matrices by $\beta=\infty$ point. Our central objects are G$\infty$E…

Probability · Mathematics 2021-12-30 Vadim Gorin , Victor Kleptsyn

The Wigner-Gaudin-Mehta-Dyson conjecture asserts that the local eigenvalue statistics of large random matrices exhibit universal behavior depending only on the symmetry class of the matrix ensemble. For invariant matrix models, the…

Probability · Mathematics 2012-01-31 Laszlo Erdos , Horng-Tzer Yau

We review and study a one-parameter family of functional transformations, denoted by $(S^{(\beta)})_{\beta\in \R}$, which, in the case $\beta<0$, provides a path realization of bridges associated to the family of diffusion processes…

Probability · Mathematics 2009-04-20 Larbi Alili , Pierre Patie

In the past decades, determinants and Pfaffians were found for eigenvalue correlations of various random matrix ensembles. These structures simplify the average over a large number of ratios of characteristic polynomials to integrations…

Mathematical Physics · Physics 2013-07-29 Mario Kieburg

We present a modified Brownian motion model for random matrices where the eigenvalues (or levels) of a random matrix evolve in "time" in such a way that they never cross each other's path. Also, owing to the exact integrability of the level…

Condensed Matter · Physics 2007-05-23 Sudhir R. Jain , Zafar Ahmed

We study the Gaussian hermitian random matrix ensemble with an external matrix which has an arbitrary number of eigenvalues with arbitrary multiplicity. We compute the limiting eigenvalues correlations when the size of the matrix goes to…

Mathematical Physics · Physics 2008-03-06 N. Orantin

Brownian motion is modelled by a harmonic oscillator (Brownian particle) interacting with a continuous set of uncoupled harmonic oscillators. The interaction is linear in the coordinates and the momenta. The model has an analytical solution…

Quantum Physics · Physics 2019-08-17 Diego G. Arbo , Mario A. Castagnino , Fabian H. Gaioli , Sergio Iguri

We study exclusion processes on the integer lattice in which particles change their velocities due to stickiness. Specifically, whenever two or more particles occupy adjacent sites, they stick together for an extended period of time, and…

Probability · Mathematics 2016-08-11 Miklós Z. Rácz , Mykhaylo Shkolnikov

We study the Dyson-Ornstein-Uhlenbeck diffusion process, an evolving gas of interacting particles. Its invariant law is the beta Hermite ensemble of random matrix theory, a non-product log-concave distribution. We explore the convergence to…

Probability · Mathematics 2023-01-16 Jeanne Boursier , Djalil Chafaï , Cyril Labbé

We consider a particle moving in one dimension, its velocity being a reversible diffusion process, with constant diffusion coefficient, of which the invariant measure behaves like $(1+|v|)^{-\beta}$ for some $\beta>0$. We prove that, under…

Probability · Mathematics 2018-05-25 Nicolas Fournier , Camille Tardif

Putting dynamics into random matrix models leads to finitely many nonintersecting Brownian motions on the real line for the eigenvalues, as was discovered by Dyson. Applying scaling limits to the random matrix models, combined with Dyson's…

Probability · Mathematics 2013-06-06 Mark Adler , Mattia Cafasso , Pierre van Moerbeke

We define a new matrix-valued stochastic process with independent stationary increments from the Laguerre Unitary Ensemble, which in a certain sense may be considered a matrix generalisation of the gamma process. We show that eigenvalues of…

Mathematical Physics · Physics 2019-03-04 J. R. Ipsen

Diffusion is the macroscopic manifestation of disordered molecular motion. Mathematically, diffusion equations are partial differential equations describing the fluid-like large-scale dynamics of parcels of molecules. Spatially…

Fluid Dynamics · Physics 2018-10-26 F. Sattin , A. Bonato , L. Salasnich

We construct a class of one-dimensional diffusion processes on the particles of branching Brownian motion that are symmetric with respect to the limits of random martingale measures. These measures are associated with the extended extremal…

Probability · Mathematics 2018-11-07 Sebastian Andres , Lisa Hartung

In the regime where the parameter beta is proportional to the reciprocal of the system size, it is known that the empirical distribution of Gaussian beta ensembles (resp.\ beta Laguerre ensembles) converges to a probability measure of…

Probability · Mathematics 2023-05-22 Fumihiko Nakano , Hoang Dung Trinh , Khanh Duy Trinh

The $\beta$ ensembles are a class of eigenvalue probability densities which generalise the invariant ensembles of classical random matrix theory. In the case of the Gaussian and Laguerre weights, the corresponding eigenvalue densities are…

Mathematical Physics · Physics 2018-12-20 Peter J. Forrester , Allan K. Trinh

Consider $D$ random systems that are modeled by independent $N\times N$ complex Hermitian Wigner matrices. Suppose they are lying on a circle and the neighboring systems interact with each other through a deterministic matrix $A$. We prove…

Probability · Mathematics 2025-02-19 Bertrand Stone , Fan Yang , Jun Yin