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We analyze quantal Brownian motion in $d$ dimensions using the unified model for diffusion localization and dissipation, and Feynman-Vernon formalism. At high temperatures the propagator possess a Markovian property and we can write down an…

Condensed Matter · Physics 2009-10-31 Doron Cohen

Nonreciprocal effective interaction forces can occur between mesoscopic particles in colloidal suspensions that are driven out of equilibrium. These forces violate Newton's third law actio=reactio on coarse-grained length and time scales.…

Soft Condensed Matter · Physics 2016-01-20 Jörg Bartnick , Marco Heinen , Alexei V Ivlev , Hartmut Löwen

We study interacting Brownian particles on the half-line whose interaction occurs through boundary local times at the origin. The particle system is given by \[ X_i^n(t)=X^n_{0,i}+W_i^n(t)+L_i^n(t) +\frac{1}{n-1}\sum_{j\ne…

Probability · Mathematics 2026-05-05 Rami Atar

This paper reviews and extends some recent results on the multivariate fractional Brownian motion (mfBm) and its increment process. A characterization of the mfBm through its covariance function is obtained. Similarly, the correlation and…

The exact analytical expressions for the time-dependent cross-correlations of the translational and rotational Brownian displacements of a particle with arbitrary shape were derived by us in [J. Chem. Phys. 142, 214902 (2015) and 144,…

Soft Condensed Matter · Physics 2018-10-09 B. Cichocki , M. L. Ekiel-Jezewska , E. Wajnryb

Fractional Brownian motion is a Gaussian process x(t) with zero mean and two-time correlations <x(t)x(s)> ~ t^{2H} + s^{2H} - |t-s|^{2H}, where H, with 0<H<1 is called the Hurst exponent. For H = 1/2, x(t) is a Brownian motion, while for H…

Statistical Mechanics · Physics 2013-05-29 Kay Jörg Wiese , Satya N. Majumdar , Alberto Rosso

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

Brownian yet non-Gaussian phenomenon has recently been observed in many biological and active matter systems. The main idea of explaining this phenomenon is to introduce a random diffusivity for particles moving in inhomogeneous…

Statistical Mechanics · Physics 2022-01-19 Xudong Wang , Yao Chen

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 study the time evolution of a chain of nonlinear oscillators. We focus on the fractal features of the spectral entropy and analyze its characteristic intermediate timescales as a function of the nonlinear coupling. A Brownian motion is…

Statistical Mechanics · Physics 2009-11-07 A. Scardicchio , P. Facchi , S. Pascazio

We consider the noncolliding Brownian motion (BM) with $N$ particles starting from the eigenvalue distribution of Gaussian unitary ensemble (GUE) of $N \times N$ Hermitian random matrices with variance $\sigma^2$. We prove that this process…

Probability · Mathematics 2015-12-18 Makoto Katori

Fractional Brownian motion belongs to a class of long memory Gaussian processes that can be represented as linear functionals of an infinite dimensional Markov process. This representation leads naturally to: - An efficient algorithm to…

Probability · Mathematics 2007-05-23 Philippe Carmona , Laure Coutin

The Bessel process with parameter $D>1$ and the Dyson model of interacting Brownian motions with coupling constant $\beta >0$ are extended to the processes in which the drift term and the interaction terms are given by the logarithmic…

Probability · Mathematics 2016-10-11 Makoto Katori

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

We study the global fluctuations for a class of determinantal point processes coming from large systems of non-colliding processes and non-intersecting paths. Our main assumption is that the point processes are constructed by biorthogonal…

Mathematical Physics · Physics 2015-12-22 Maurice Duits

This paper studies the intermediate time behaviour of a small random perturbation of a periodic cellular flow. Our main result shows that on time scales shorter than the diffusive time scale, the limiting behaviour of trajectories that…

Probability · Mathematics 2016-09-09 Martin Hairer , Gautam Iyer , Leonid Koralov , Alexei Novikov , Zsolt Pajor-Gyulai

Consider a periodically forced nonlinear system which can be presented as a collection of smaller subsystems with pairwise interactions between them. Each subsystem is assumed to be a massive point moving with friction on a compact surface,…

Dynamical Systems · Mathematics 2015-09-25 Ivan Polekhin

In this expository note we highlight the correlation function method as a unified approach in proving both hydrodynamic limits and fluctuation limits for reaction diffusion particle systems. For simplicity we focus on the case when the…

Probability · Mathematics 2021-01-12 Wai-Tong Louis Fan

In this review we deal with open (dissipative and stochastic) quantum systems within the Bohmian mechanics framework which has the advantage to provide a clear picture of quantum phenomena in terms of trajectories, originally in…

Quantum Physics · Physics 2022-08-10 S. V. Mousavi , S. Miret-Artes

We use computer simulations to test a simple idea for mapping between long-time self diffusivities obtained from molecular and Brownian dynamics. The strategy we explore is motivated by the behavior of fluids comprising particles that…

Soft Condensed Matter · Physics 2011-10-25 Mark J. Pond , Jeffrey R. Errington , Thomas M. Truskett