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Since the introduction of Dyson's Brownian motion in early 1960's, there have been a lot of developments in the investigation of stochastic processes on the space of Hermitian matrices. Their properties, especially, the properties of their…

Probability · Mathematics 2021-09-28 Jian Song , Jianfeng Yao , Wangjun Yuan

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 consider the Markov random flight $\bold X(t)$ in the Euclidean space $\Bbb R^m, \; m\ge 2,$ starting from the origin $\bold 0\in\Bbb R^m$ that, at Poisson-paced times, changes its direction at random according to arbitrary distribution…

Probability · Mathematics 2016-05-23 Alexander D. Kolesnik

Dynamics simulations of constrained particles can greatly aid in understanding the temporal and spatial evolution of biological processes such as lateral transport along membranes and self-assembly of viruses. Most theoretical efforts in…

Computational Physics · Physics 2017-03-03 Stefan Paquay , Remy Kusters

The multivariate Ornstein-Uhlenbeck process is used in many branches of science and engineering to describe the regression of a system to its stationary mean. Here we present an $O(N)$ Bayesian method to estimate the drift and diffusion…

Statistical Mechanics · Physics 2018-08-01 Rajesh Singh , Dipanjan Ghosh , R. Adhikari

\noindent Consider an infinite collection of particles on the real line moving according to independent Brownian motions and such that the $i$-th particle from the left gets the drift $g_{i-1}$. The case where $g_0=1$ and $g_{i}=0$ for all…

Probability · Mathematics 2024-07-09 Sayan Banerjee , Amarjit Budhiraja

In this thesis, branching Brownian motion (BBM) is a random particle system where the particles diffuse on the real line according to Brownian motions and branch at constant rate into a random number of particles with expectation greater…

Probability · Mathematics 2013-04-02 Pascal Maillard

In this article, using kernel convolution of order based dependent Dirichlet process (Griffin and Steel (2006)) we construct a nonstationary, nonseparable, nonparametric space-time process, which, as we show, satisfies desirable properties,…

Methodology · Statistics 2020-05-04 Moumita Das , Sourabh Bhattacharya

In the L\'evy construction of Brownian motion, a Haar-derived basis of functions is used to form a finite-dimensional process $W^{N}$ and to define the Wiener process as the almost sure path-wise limit of $W^{N}$ when $N$ tends to infinity.…

Probability · Mathematics 2008-06-10 Thibaud Taillefumier

In the field of Markov models for image generation, the main idea is to learn how non-trivial images are gradually destroyed by a trivial forward Markov dynamics over the large time window $[0,t]$ converging towards pure noise for $t \to +…

Statistical Mechanics · Physics 2025-01-30 Cecile Monthus

A discrete model of Brownian sticky flows on the unit circle is described: it is constructed with products of Beta matrices on the discrete torus. Sticky flows are defined by their ``moments'' which are consistent systems of transition…

Probability · Mathematics 2007-05-23 Yves Le Jan , Sophie Lemaire

The Burnside process is a classical Markov chain for sampling uniformly from group orbits. We introduce the dual Burnside process, obtained by interchanging the roles of group elements and states. This dual chain has stationary law…

Probability · Mathematics 2026-05-22 Ivan Z. Feng

We consider Brownian motions with one-sided collisions, meaning that each particle is reflected at its right neighbour. For a finite number of particles a Sch\"{u}tz-type formula is derived for the transition probability. We investigate an…

Mathematical Physics · Physics 2015-04-23 Patrik L. Ferrari , Herbert Spohn , Thomas Weiss

Two families of stochastic interacting particle systems, the interacting Brownian motions and Bessel processes, are defined as extensions of Dyson's Brownian motion models and the eigenvalue processes of the Wishart and Laguerre processes…

Mathematical Physics · Physics 2014-06-09 Sergio Andraus

The trace of a Markov process is the time changed process of the original process on the support of the Revuz measure used in the time change. In this paper, we will concentrate on the reflecting Brownian motions on certain closed strips.…

Probability · Mathematics 2021-09-08 Liping Li , Wenjie Sun

We introduce methods for large scale Brownian Dynamics (BD) simulation of many rigid particles of arbitrary shape suspended in a fluctuating fluid. Our method adds Brownian motion to the rigid multiblob method at a cost comparable to the…

Soft Condensed Matter · Physics 2018-01-17 B. Sprinkle , F. Balboa Usabiaga , N. A. Patankar , A. Donev

We introduce a general method for transforming the equations of motion following from a Das-Jevicki-Sakita Hamiltonian, with boundary conditions, into a boundary value problem in one-dimensional quantum mechanics. For the particular case of…

High Energy Physics - Theory · Physics 2009-10-31 L. D. Paniak

Semimartingale reflecting Brownian motions (SRBMs) are diffusion processes with state space the d-dimensional nonnegative orthant, in the interior of which the processes evolve according to a Brownian motion, and that reflect against the…

Probability · Mathematics 2010-11-13 Maury Bramson

This work gives sufficient conditions for uniqueness in law of semimartingale, obliquely reflecting Brownian motion in a nonpolyhedral, piecewise ${\cal C}^2$ cone, with radially constant, Lipschitz continuous direction of reflection on…

Probability · Mathematics 2025-01-27 Cristina Costantini

We introduce a variational theory for processes adapted to the multi-dimensional Brownian motion filtration. The theory provides a differential structure which describes the infinitesimal evolution of Wiener functionals at very small…

Probability · Mathematics 2017-07-13 Alberto Ohashi , Dorival Leão , Alexandre B. Simas
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