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We consider oscillatory systems of interacting Hawkes processes introduced in Ditlevsen and Loecherbach (2017) to model multi-class systems of interacting neurons together with the diffusion approximations of their intensity processes. This…

Probability · Mathematics 2017-09-28 Eva Löcherbach

For diffusion processes in dimension $d>1$, the statistics of trajectory observables over the time-window $[0,T]$ can be studied via the Feynman-Kac deformations of the Fokker-Planck generator, that can be interpreted as euclidean…

Statistical Mechanics · Physics 2024-01-22 Cecile Monthus

In many-particle diffusions, particles that move the furthest and fastest can play an outsized role in physical phenomena. A theoretical understanding of the behavior of such extreme particles is nascent. A classical model, in the spirit of…

Statistical Mechanics · Physics 2024-11-22 Jacob B. Hass , Aileen N. Carroll-Godfrey , Eric I. Corwin , Ivan Z. Corwin

Diffusion of impenetrable particles in a crowded one-dimensional channel is referred as the single file diffusion. The particles do not pass each other and the displacement of each individual particle is sub-diffusive. We analyse a simple…

Statistical Mechanics · Physics 2016-04-18 Tridib Sadhu , Bernard Derrida

This article examines large time behaviour of finite state mean-field interacting particle systems. Our first main result is a sharp estimate (in the exponential scale) on the time required for convergence of the empirical measure process…

Probability · Mathematics 2021-03-02 Sarath Yasodharan , Rajesh Sundaresan

We apply the macroscopic fluctuation theory (MFT) to study the large-scale dynamical properties of Brownian particles with arbitrary pairwise interaction. By combining it with standard results of equilibrium statistical mechanics for the…

Statistical Mechanics · Physics 2026-05-19 Aurélien Grabsch , Davide Venturelli , Olivier Bénichou

Diffusion-coagulation can be simply described by a dynamic where particles perform a random walk on a lattice and coalesce with probability unity when meeting on the same site. Such processes display non-equilibrium properties with strong…

Statistical Mechanics · Physics 2018-03-13 L. Turban , J. -Y. Fortin

Abridged abstract: Inert interactions between randomly moving entities and spatial disorder play a crucial role in quantifying the diffusive properties of a system. These interactions affect only the movement of the entities, and examples…

Statistical Mechanics · Physics 2022-09-20 Seeralan Sarvaharman , Luca Giuggioli

The effect of introducing a mass dependent diffusion rate ~ m^{-alpha} in a model of coagulation with single-particle break up is studied both analytically and numerically. The model with alpha=0 is known to undergo a nonequilibrium phase…

Statistical Mechanics · Physics 2009-11-07 R. Rajesh , Dibyendu Das , Bulbul Chakraborty , Mustansir Barma

We study the large deviation behavior of a system of diffusing particles with a mean field interaction, described through a collection of stochastic differential equations, in which each particle is driven by a vanishing independent…

Probability · Mathematics 2021-08-10 Amarjit Budhiraja , Michael Conroy

Systems driven far from equilibrium may exhibit anomalous density fluctuations: active matter with orientational order display giant density fluctuations at large scale, while systems of interacting particles close to an absorbing phase…

Statistical Mechanics · Physics 2026-03-23 Sara Dal Cengio , Romain Mari , Eric Bertin

We study the diffusion of a particle with a time-dependent diffusion constant $D(t)$ that switches between random values drawn from a distribution $W(D)$ at a fixed rate $r$. Using a renewal approach, we compute exactly the moments of the…

Statistical Mechanics · Physics 2025-08-06 Mathis Guéneau , Satya N. Majumdar , Gregory Schehr

We investigate large deviations for the empirical measure of the forward and backward recurrence time processes associated with a classical renewal process with arbitrary waiting-time distribution. The Donsker-Varadhan theory cannot be…

Probability · Mathematics 2010-09-22 Raphael Lefevere , Mauro Mariani , Lorenzo Zambotti

We formulate large deviations principle (LDP) for diffusion pair $(X^\epsilon,\xi^\epsilon)=(X_t^\epsilon,\xi_t^\epsilon)$, where first component has a small diffusion parameter while the second is ergodic Markovian process with fast time.…

Probability · Mathematics 2007-05-23 R. Liptser

Understanding transport processes in complex nanoscale systems, like ionic conductivities in nanofluidic devices or heat conduction in low dimensional solids, poses the problem of examining fluctuations of currents within nonequilibrium…

Mesoscale and Nanoscale Physics · Physics 2021-08-04 David T. Limmer , Chloe Y. Gao , Anthony R. Poggioli

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

The dynamics of interacting particles in orbital magnetic fields are notoriously difficult to study, as this physics is inherently connected to electronic correlations in two-dimensional systems, for which no straightforward theoretical…

Quantum Gases · Physics 2026-03-27 Łukasz Iwanek , Marcin Mierzejewski , Adam S. Sajna

We obtain large deviation results for a two time-scale model of jump-diffusion processes. The processes on the two time scales are fully inter-dependent, the slow process has small perturbative noise and the fast process is ergodic. Our…

Probability · Mathematics 2016-09-19 Rohini Kumar , Lea Popovic

We consider a random diffusion dynamics for an infinite system of hard spheres of two different sizes evolving in $\mathbb{R}^d$, its reversible probability measure, and its projection on the subset of the large spheres. The main feature is…

Probability · Mathematics 2024-03-05 Myriam Fradon , Julian Kern , Sylvie Roelly , Alexander Zass

Superslow diffusion, i.e., the long-time diffusion of particles whose mean-square displacement (variance) grows slower than any power of time, is studied in the framework of the decoupled continuous-time random walk model. We show that this…

Statistical Mechanics · Physics 2010-11-24 S. I. Denisov , H. Kantz