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As a first step toward a characterization of the limiting extremal process of branching Brownian motion, we proved in a recent work [Comm. Pure Appl. Math. 64 (2011) 1647-1676] that, in the limit of large time $t$, extremal particles…

Probability · Mathematics 2012-09-25 Louis-Pierre Arguin , Anton Bovier , Nicola Kistler

Active Brownian motion commonly assumes spherical overdamped particles. However, self-propelled particles are often neither symmetric nor overdamped yet underlie random fluctuations from their surroundings. Active Brownian motion has…

Soft Condensed Matter · Physics 2022-10-03 Jonas Mayer Martins , Raphael Wittkowski

A novel principle is presented which allows for the proof of bounded weak solutions to a class of physically relevant, strongly coupled parabolic systems exhibiting a formal gradient-flow structure. The main feature of these systems is that…

Analysis of PDEs · Mathematics 2015-06-11 Ansgar Jüngel

The effects of a dispersed particulate phase on the onset of Rayleigh-B\'enard convection in a fluid layer is studied theoretically by means of a two-fluid Eulerian modelization. The particles are non-Brownian, spherical, with inertia and…

Fluid Dynamics · Physics 2024-12-24 Saad Raza , Silvia C. Hirata , Enrico Calzavarini

We consider the Fleming-Viot particle system consisting of $N$ identical particles evolving in $\mathbb{R}_{>0}$ as Brownian motions with constant drift $-1$. Whenever a particle hits $0$, it jumps onto another particle in the interior. It…

Probability · Mathematics 2023-06-07 Oliver Tough

We investigate recurrence and transience of Branching Markov Chains (BMC) in discrete time. Branching Markov Chains are clouds of particles which move (according to an irreducible underlying Markov Chain) and produce offspring…

Probability · Mathematics 2016-09-07 Nina Gantert , Sebastian Mueller

We consider a Brownian particle, with diffusion constant D, moving inside an expanding d-dimensional sphere whose surface is an absorbing boundary for the particle. The sphere has initial radius L_0 and expands at a constant rate c. We…

Statistical Mechanics · Physics 2009-11-13 Alan J Bray , Richard Smith

We prove large deviations principles in large time, for the Brownian occupation time in random scenery. The random scenery is constant on unit cubes, and consist of i.i.d. bounded variables, independent of the Brownian motion. This model is…

Probability · Mathematics 2007-05-23 A. Asselah , F. Castell

Simultaneous diffusive and inertial motion of Brownian particles in laminar Couette flow is investigated via Lagrangian and Eulerian descriptions to determine the effect of particle inertia on diffusive transport in the long-time. The…

Statistical Mechanics · Physics 2010-08-13 Yannis Drossinos , Michael W. Reeks

We prove that the extremal process of branching Brownian motion, in the limit of large times, converges weakly to a cluster point process. The limiting process is a (randomly shifted) Poisson cluster process, where the positions of the…

Probability · Mathematics 2011-03-14 Louis-Pierre Arguin , Anton Bovier , Nicola Kistler

We focus on the dynamics of a Brownian particle whose mass fluctuates. First we show that the behaviour is similar to that of a Brownian particle moving in a fluctuating medium, as studied by Beck [Phys. Rev. Lett. 87 (2001) 180601]. By…

Statistical Mechanics · Physics 2007-06-13 R. Lambiotte , M. Ausloos

Recently, we introduced the active Dyson Brownian motion model (DBM), in which $N$ run-and-tumble particles interact via a logarithmic repulsive potential in the presence of a harmonic well. We found that in a broad range of parameters the…

Statistical Mechanics · Physics 2024-11-08 Leo Touzo , Pierre Le Doussal , Gregory Schehr

In this paper, we investigate the optimal control problem for systems driven by mixed fractional Brownian motion (including a fractional Brownian motion with Hurst parameter $H>1/2$ and the standard Brownian motion). By using Malliavin…

Optimization and Control · Mathematics 2024-12-25 Yuhang Li , Yuecai Han

We study a system of hard rods of finite size in one space dimension, which move by Brownian noise while avoiding overlap. We consider a scaling in which the number of particles tends to infinity while the volume fraction of the rods…

Mathematical Physics · Physics 2020-05-18 Nir Gavish , Pierre Nyquist , Mark Peletier

We investigate the behaviour of a finite chain of Brownian particles, interacting through a pairwise potential $U$, with one end of the chain fixed and the other end pulled away, in the limit of slow pulling speed and small Brownian noise.…

Probability · Mathematics 2020-10-16 Frank Aurzada , Volker Betz , Mikhail Lifshits

Diffusion of small particles is omnipresent in a plentiful number of processes occurring in Nature. As such, it is widely studied and exerted in almost all branches of sciences. It constitutes such a broad and often rather complex subject…

Statistical Mechanics · Physics 2023-01-11 Jakub Spiechowicz , Ivan G. Marchenko , Peter Hänggi , Jerzy Łuczka

In two prior papers of this series, it was proposed that a wavefunction model of a heavy particle and a collection of light particles might generate ``Brownian-Motion-Like" trajectories as well as diffusive motion (displacement proportional…

Quantum Physics · Physics 2025-09-16 Leonardo De Carlo , W. David Wick

We introduce a system of Brownian particles, each absorbed upon hitting an associated moving boundary. The boundaries are determined by the conditional probabilities of the particles being absorbed before some final time horizon, given the…

Probability · Mathematics 2025-10-06 Philipp Jettkant , Andreas Sojmark

Density-dependent diffusion is a widespread phenomenon in nature. We have examined the density-dependent diffusion behavior of some biological processes such as tumor growth and invasion [23]. Here, we extend our previous work by developing…

Statistical Mechanics · Physics 2022-02-14 Ahmed M. Fouad , Marwa M. Fouad

This paper presents a new method for conditional probability density simulation. The method is design to work with unstructured data set when data are not characterized by the same covariates yet share common information. Specific examples…

Methodology · Statistics 2025-08-05 Esteban G. Tabak , Giulio Trigila , Wenjun Zhao