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Central limit theorems for random walks in quenched random environments have attracted plenty of attention in the past years. More recently still, finer local limit theorems -- yielding a Gaussian density multiplied by a highly oscillatory…

Probability · Mathematics 2013-03-07 Mikko Stenlund

We study the motion of an inertial particle in a fractional Gaussian random field. The motion of the particle is described by Newton's second law, where the force is proportional to the difference between a background fluid velocity and the…

Dynamical Systems · Mathematics 2012-03-20 Georg Schöchtel

Assuming an effective quadratic Hamiltonian, we derive an approximate, linear stochastic equation of motion for the density-fluctuations in liquids, composed of overdamped Brownian particles. From this approach, time dependent two point…

Soft Condensed Matter · Physics 2017-04-26 Matthias Krüger , David S. Dean

The velocity of a passive particle in a one-dimensional wave field is shown to converge in law to a Wiener process, in the limit of a dense wave spectrum with independent complex amplitudes, where the random phases distribution is invariant…

Mathematical Physics · Physics 2012-07-12 Yves Elskens

We prove a quenched local central limit theorem for continuous-time random walks in $\mathbb Z^d, d\ge 2$, in a uniformly-elliptic time-dependent balanced random environment which is ergodic under space-time shifts. We also obtain Gaussian…

Probability · Mathematics 2019-12-04 Jean-Dominique Deuschel , Xiaoqin Guo

We consider the motion of a particle under a continuum random environment whose distribution is given by the Howitt-Warren flow. In the moderate deviation regime, we establish that the quenched density of the motion of the particle (after…

Probability · Mathematics 2024-12-24 Sayan Das , Hindy Drillick , Shalin Parekh

We consider the motion of a particle governed by a weakly random Hamiltonian flow. We identify temporal and spatial scales on which the particle trajectory converges to a spatial Brownian motion. The main technical issue in the proof is to…

Mathematical Physics · Physics 2009-11-11 T. Komorowski , L. Ryzhik

Completing the study initiated by Mounaix and Collet [J. Stat. Phys. {\bf 143}, 139-147 (2011)], we investigate the realizations of a Gaussian random field in the limit where a given (general) quadratic form of the field is large.…

Mathematical Physics · Physics 2015-09-15 Philippe Mounaix

We study a simple model for the trajectory of a particle in a turbulent fluid, where a Brownian motion travels through a random Gaussian velocity field. We study the quenched law of the process and prove that in a weak environment setting,…

Probability · Mathematics 2022-08-26 Dom Brockington , Jon Warren

This paper studies particle propagation in a one-dimensional inhomogeneous medium where the laws of motion are generated by chaotic and deterministic local maps. Assuming that the particle's initial location is random and uniformly…

Probability · Mathematics 2011-10-18 Lasse Leskelä , Mikko Stenlund

We prove a central limit theorem for the momentum distribution of a particle undergoing an unbiased spatially periodic random forcing at exponentially distributed times without friction. The start is a linear Boltzmann equation for the…

Mathematical Physics · Physics 2015-05-14 Jeremy Clark , Christian Maes

We prove the quenched version of the central limit theorem for the displacement of a random walk in doubly stochastic random environment, under the $H_{-1}$-condition, with slightly stronger, $L^{2+\varepsilon}$ (rather than $L^2$)…

Probability · Mathematics 2017-10-03 Bálint Tóth

We study the stochastic motion of a particle subject to spatially varying Lorentz force in the small-mass limit. The limiting procedure yields an additional drift term in the overdamped equation that cannot be obtained by simply setting…

Soft Condensed Matter · Physics 2019-09-04 Hidde Derk Vuijk , Joseph Michael Brader , Abhinav Sharma

We consider the stochastic target problem of finding the collection of initial laws of a mean-field stochastic differential equation such that we can control its evolution to ensure that it reaches a prescribed set of terminal probability…

Probability · Mathematics 2018-11-01 Bruno Bouchard , Boualem Djehiche , Idris Kharroubi

We consider a stochastic flow driven by a finite dimensional Brownian motion. We show that almost every realization of such a flow exhibits strong statistical properties such as the exponential convergence of an initial measure to the…

Probability · Mathematics 2007-05-23 Dmitry Dolgopyat , Vadim Kaloshin , Leonid Koralov

We study a one-dimensional model for heavy particles in a compressible fluid. The fluid-velocity field is modelled by a persistent Gaussian random function, and the particles are assumed to be weakly inertial. Since one-dimensional…

Fluid Dynamics · Physics 2019-08-06 J. Meibohm , B. Mehlig

In the framework of a stochastic picture for the one-dimensional branching Brownian motion, we compute the probability density of the number of particles near the rightmost one at a time $T$, that we take very large, when this extreme…

Statistical Mechanics · Physics 2022-12-13 Anh Dung Le , Alfred H. Mueller , Stéphane Munier

We consider the long-time behavior of a diffusion process on $\mathbb{R}^d$ advected by a stationary random vector field which is assumed to be divergence-free, dihedrally symmetric in law and have a log-correlated potential. A special case…

Probability · Mathematics 2024-09-19 Scott Armstrong , Ahmed Bou-Rabee , Tuomo Kuusi

Assume that a stochastic processes can be approximated, when some scale parameter gets large, by a fluid limit (also called "mean field limit", or "hydrodynamic limit"). A common practice, often called the "fixed point approximation"…

Dynamical Systems · Mathematics 2022-06-28 Jean-Yves Le Boudec

We prove a local limit theorem, i.e. a central limit theorem for densities, for a sequence of independent and identically distributed random variables taking values on an abstract Wiener space; the common law of those random variables is…

Probability · Mathematics 2016-10-05 Alberto Lanconelli , Aurel Iulian Stan
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