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Brownian dynamics play a key role in understanding the diffusive transport of micro particles in a bounded environment. In geometries containing confining walls, physical laws determine the behavior of the random trajectories at the…

Statistical Mechanics · Physics 2018-08-15 Alain Mazzolo

For some discrete parameters $k\ge0$, multivariate (Dunkl-)Bessel processes on Weyl chambers $C$ associated with root systems appear as projections of Brownian motions without drift on Euclidean spaces $V$, and the associated transition…

Probability · Mathematics 2025-12-12 Michael Voit

Renyi's "thinning" operation on a discrete random variable is a natural discrete analog of the scaling operation for continuous random variables. The properties of thinning are investigated in an information-theoretic context, especially in…

Information Theory · Computer Science 2010-08-17 Peter Harremoes , Oliver Johnson , Ioannis Kontoyiannis

We prove an infinite dimensional integration by parts formula on the law of the modulus of the Brownian bridge $BB=(BB_t)_{0 \leq t \leq 1}$ from $0$ to $0$ in use of methods from white noise analysis and Dirichlet form theory. Additionally…

Probability · Mathematics 2017-06-23 Martin Grothaus , Robert Voßhall

We consider a structural stochastic volatility model for the loss from a large portfolio of credit risky assets. Both the asset value and the volatility processes are correlated through systemic Brownian motions, with default determined by…

Probability · Mathematics 2026-03-24 Ben Hambly , Nikolaos Kolliopoulos

An angular time-dependent probability density function describing Brownian or anomalous rotational dynamics of fixed-length atom-to-atom vectors is presented. The probability density function, which fully incorporates angular boundary…

Other Condensed Matter · Physics 2023-03-07 David A. Faux , Örs Istók , Arifah A. Rahaman , Peter J. McDonald , Eoin McKiernan , Dermot F. Brougham

The purpose of the article is twofold. Firstly, we review some recent results on the maximum likelihood estimation in the regression model of the form $X_t = \theta G(t) + B_t$, where $B$ is a Gaussian process, $G(t)$ is a known function,…

Probability · Mathematics 2018-12-27 Yuliya Mishura , Kostiantyn Ralchenko , Sergiy Shklyar

We show that simple explicit formulas can be obtained for several relevant quantities related to the laws of the uniformly sampled Brownian bridge, Brownian meander and three dimensional Bessel process. To prove such results, we use the…

Probability · Mathematics 2013-11-11 Mathieu Rosenbaum , Marc Yor

Recently, it has been shown that stochastic spatial Lotka-Volterra models when suitably rescaled can converge to a super Brownian motion. We show that the limit process could be a super stable process if the kernel of the underlying motion…

Probability · Mathematics 2009-02-05 Hui He

This study deals with continuous limits of interacting one-dimensional diffusive systems, arising from stochastic distortions of discrete curves with various kinds of coding representations. These systems are essentially of a…

Statistical Mechanics · Physics 2011-09-09 Guy Fayolle , Cyril Furtlehner

For refracted skew Brownian motion (skew Brownian motion with two-valued drift), adopting a perturbation approach we find expressions of its potential densities. As applications, we recover its transition density and study its long-time…

Probability · Mathematics 2025-04-08 Zaniar Ahmadi , Xiaowen Zhou

A nonequilibrium fluctuation theorem is established for a colloidal particle driven by an external force within the hydrodynamic theory of Brownian motion, describing hydrodynamic memory effects such as the t^(-3/2) power-law decay of the…

Statistical Mechanics · Physics 2020-06-24 Pierre Gaspard

We investigate the validity of the Markovian assumption in modeling near-wall turbulence by analyzing the detachment of micron-sized particles from the viscous sublayer. By coupling direct numerical simulations with a fractional…

Fluid Dynamics · Physics 2026-04-15 David Ben-Shlomo , Ronen Berkovich , Eyal Fattal

Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or engineering applications. Since many areas, such as biology or discrete-event systems, are…

Machine Learning · Computer Science 2021-09-30 Lukas Köhs , Bastian Alt , Heinz Koeppl

We give a Dirichlet form approach for the construction of a distorted Brownian motion in $E:=[0,\infty)^n$, $n\in\mathbb{N}$, where the behavior on the boundary is determined by the competing effects of reflection from and pinning at the…

Probability · Mathematics 2014-09-26 Torben Fattler , Martin Grothaus , Robert Voßhall

We study interacting systems of linear Brownian motions whose drift vector at every time point is determined by the relative ranks of the coordinate processes at that time. Our main objective has been to study the long range behavior of the…

Probability · Mathematics 2008-01-22 Soumik Pal , Jim Pitman

Inspired by the recent work of Bertini and Posta, who introduced the boundary driven Brownian gas on $[0,1]$, we study boundary driven systems of independent particles in a general setting, including particles jumping on finite graphs and…

Probability · Mathematics 2021-12-24 Gioia Carinci , Simone Floreani , Cristian Giardinà , Frank Redig

We raise a question on whether a dynamical system driven by Markov process is Markovian, for which we are able to propose a criterion and examples of positive case. This investigation leads us to develop (i) a general construction of…

Probability · Mathematics 2019-08-22 Motoya Machida

We determine the rate of decay of the expectation Z(t) of some multiplicative functional related to Brownian motion up to time t. This permits to prove that the Wiener measure, penalized by this multiplicative functional, converges as t…

Probability · Mathematics 2007-05-23 Bernard Roynette , Pierre Vallois , Marc Yor

The analysis of dynamical systems is a fundamental tool in the natural sciences and engineering. It is used to understand the evolution of systems as large as entire galaxies and as small as individual molecules. With predefined conditions…

Machine Learning · Statistics 2024-12-19 Ludwig Winkler
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