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We perform detailed computational and experimental measurements of the driven dynamics of a dense, uniform suspension of sedimented microrollers driven by a magnetic field rotating around an axis parallel to the floor. We develop a…

Soft Condensed Matter · Physics 2020-07-03 Brennan Sprinkle , Ernest B. van der Wee , Yixiang Luo , Michelle Driscoll , Aleksandar Donev

The spatial components of the autocorrelation function of noninteracting dipoles are analytically obtained in terms of rotational Brownian motion on the surface of a unit sphere using multi-level jumping formalism based on Debye's…

Statistical Mechanics · Physics 2009-09-10 Ekrem Aydiner

The purpose of this note is to collect in one place a few results about simple random walk and Brownian motion which are often useful. These include standard results such as Beurling estimates, large deviation estimates, and a method for…

Probability · Mathematics 2007-05-23 Christian Benes

We study a correlated Brownian motion in two dimensions, which is reflected, stopped or killed in a wedge represented as the intersection of two half spaces. First, we provide explicit density formulas, hinted by the method of images. These…

Probability · Mathematics 2022-12-15 Pierre Bras , Arturo Kohatsu-Higa

We consider non degenerate Brownian SDEs with H{\"o}lder continuous in space diffusion coefficient and unbounded drift with linear growth. We derive two sided bounds for the associated density and pointwise controls of its derivatives up to…

Analysis of PDEs · Mathematics 2020-06-15 S. Menozzi , A. Pesce , X. Zhang

This paper deals with the issue of concept drift in supervised machine learn-ing. We make use of graphical models to elicit the visible structure of the dataand we infer from there changes in the hidden context. Differently from previous…

Machine Learning · Computer Science 2021-02-03 Luigi Riso , Marco Guerzoni

For $d \geq 2$ let $B$ be standard $d$-dimensional Brownian motion. For any $\alpha < 1/d$ we construct an $\alpha$-H\"{o}lder continuous function $f \colon [0,1] \to \mathbb{R}^d$ so that the range of $B-f$ covers an open set. This…

Probability · Mathematics 2010-03-02 Tonći Antunović , Yuval Peres , Brigitta Vermesi

For Brownian motion in a (two-dimensional) wedge with negative drift and oblique reflection on the axes, we derive an explicit formula for the Laplace transform of its stationary distribution (when it exists), in terms of Cauchy integrals…

Probability · Mathematics 2020-06-11 Sandro Franceschi , Kilian Raschel

The main objective of this paper consists in creating a new class of copulae from various joint distributions occurring in connection with certain Brownian motion processes. We focus our attention on the distributions of univariate Brownian…

Statistics Theory · Mathematics 2020-04-23 Michel Adès , Matthieu Dufour , Serge B. Provost , Marie-Claude Vachon

The non-thermal nature of self-propelling colloids offers new insights into non-equilibrium physics. The central mathematical model to describe their trajectories is active Brownian motion, where a particle moves with a constant speed,…

We prove the existence of the reflected diffusion on a complex of an arbitrary size for a large class of planar simple nested fractals. Such a process is obtained as a folding projection of the free Brownian motion from the unbounded…

Probability · Mathematics 2020-01-08 Kamil Kaleta , Mariusz Olszewski , Katarzyna Pietruska-Pałuba

Brownian motion near soft surfaces is a situation widely encountered in nanoscale and biological physics. However, a complete theoretical description is lacking to date. Here, we theoretically investigate the dynamics of a two-dimensional…

Soft Condensed Matter · Physics 2025-10-01 Yilin Ye , Yacine Amarouchene , Raphaël Sarfati , David S. Dean , Thomas Salez

While many real-world data streams imply that they change frequently in a nonstationary way, most of deep learning methods optimize neural networks on training data, and this leads to severe performance degradation when dataset shift…

Machine Learning · Computer Science 2021-07-02 Wonju Lee , Seok-Yong Byun , Jooeun Kim , Minje Park , Kirill Chechil

The Brownian motion of a test particle interacting with a quantum scalar field in the presence of a perfectly reflecting boundary is studied in (1 + 1)-dimensional flat spacetime. Particularly, the expressions for dispersions in velocity…

Quantum Physics · Physics 2014-09-02 V. A. De Lorenci , E. S. Moreira , M. M. Silva

Consider the infinite Atlas model: a semi-infinite collection of particles driven by independent standard Brownian motions with zero drifts, except for the bottom-ranked particle which receives unit drift. We derive a continuum…

Probability · Mathematics 2017-06-19 Andrey Sarantsev , Li-Cheng Tsai

Prompted by an example arising in critical percolation, we study some reflected Brownian motions in symmetric planar domains and show that they are intertwined with one-dimensional diffusions. In the case of a wedge, the reflected Brownian…

Probability · Mathematics 2007-05-23 Julien Dubedat

We investigate the relationship between the effective diffusivity and effective drift of a particle moving in a random medium. The velocity of the particle combines a white noise diffusion process with a local drift term that depends…

Condensed Matter · Physics 2009-10-28 D. S. Dean , I. T. Drummond , R. R. Horgan

We consider the quickest change-point detection problem where the aim is to detect the onset of a pre-specified drift in "live"-monitored standard Brownian motion; the change-point is assumed unknown (nonrandom). The object of interest is…

Statistics Theory · Mathematics 2016-04-19 Aleksey S. Polunchenko

The area swept out under a one-dimensional Brownian motion till its first-passage time is analysed using a backward Fokker-Planck technique. We obtain an exact expression of the area distribution for the zero drift case, and provide various…

Statistical Mechanics · Physics 2009-11-11 Michael J. Kearney , Satya N. Majumdar

The notion of concept drift refers to the phenomenon that the distribution, which is underlying the observed data, changes over time; as a consequence machine learning models may become inaccurate and need adjustment. Many unsupervised…

Machine Learning · Computer Science 2022-02-22 Fabian Hinder , Valerie Vaquet , Barbara Hammer
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