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The generic feature of traffic in a network of flowing electronic data packets is a phase transition from a stationary free-flow phase to a continuously growing congested non-stationary phase. In the most simple network of directed oriented…

Statistical Mechanics · Physics 2009-11-11 G. Mukherjee , S. S. Manna

We introduce a model for diffusion of two classes of particles ($A$ and $B$) with priority: where both species are present in the same site the motion of $A$'s takes precedence over that of $B$'s. This describes realistic situations in…

Statistical Mechanics · Physics 2009-03-03 Michalis Maragakis , Shai Carmi , Daniel ben-Avraham , Shlomo Havlin , Panos Argyrakis

We compare the fluctuations in the velocity and in the fraction of time spent at a given position for minimal models of a passive and an active particle: an asymmetric random walker and a run-and-tumble particle in continuous time and on a…

Statistical Mechanics · Physics 2019-10-03 Emil Mallmin , Richard A Blythe , Martin R Evans

We provide Large Deviation estimates for the bridge of a $d$-dimensional general diffusion process as the conditioning time tends to $0$ and apply these results to the evaluation of the asymptotics of its exit time probabilities. We are…

Probability · Mathematics 2014-06-19 Paolo Baldi , Lucia Caramellino , Maurizia Rossi

We investigate fluctuations in the average speed or current of a self-interacting diffusion (SID) on a ring, mimicking the non-Markovian behaviour of an agent influenced by its own path. We derive the SID's phase diagram, showing a…

Statistical Mechanics · Physics 2024-12-16 Francesco Coghi

The position $x(t)$ of a particle diffusing in a one-dimensional uncorrelated and time dependent random medium is simply Gaussian distributed in the typical direction, i.e. along the ray $x=v_0 t$, where $v_0$ is the average drift. However,…

Statistical Mechanics · Physics 2021-08-05 Guillaume Barraquand , Pierre Le Doussal

Drifting models are capable one-step generative models trained to follow a drifting field. The field combines attractive and repulsive softmax-weighted centroids over the data and current-generator distributions. In practice, only a…

Machine Learning · Computer Science 2026-05-01 Jiaru Zhang , Zeyun Deng , Juanwu Lu , Ziran Wang , Ruqi Zhang

We consider stochastic control with discretionary stopping for the drift of a diffusion process over an infinite time horizon. The objective is to choose a control process and a stopping time to minimize the expectation of a convex terminal…

Optimization and Control · Mathematics 2025-06-24 Václav E. Beneš , Georgy Gaitsgori , Ioannis Karatzas

The problem of reconstructing the drift of a diffusion in $\erre^d$, $d\geq 2$, from the transition probability density observed outside a domain is considered. The solution of this problem also solves a new inverse problem for a class of…

Probability · Mathematics 2007-06-13 Sergio Albeverio , Carlo Marinelli

We study the diffusion of an ensemble of overdamped particles sliding over a tilted random poten- tial (produced by the interaction of a particle with a random polymer) with long-range correlations. We found that the diffusion properties of…

Disordered Systems and Neural Networks · Physics 2014-04-11 R. Salgado-Garcia , Cesar Maldonado

We consider the correlations and the hydrodynamic description of random walkers with a general finite memory moving on a $d$ dimensional hypercubic lattice. We derive a drift-diffusion equation and identify a memory-dependent critical…

Statistical Mechanics · Physics 2020-01-29 Eial Teomy , Ralf Metzler

The aim of this paper is to derive the averaged governing equations for non-degenerated oscillatory flows, in which the magnitudes of mean velocity and oscillating velocity are similar. We derive the averaged equations for a scalar passive…

Fluid Dynamics · Physics 2011-10-31 Vladimir A Vladimirov

We study the time-averaged flow in a model of particles that randomly hop on a finite directed graph. In the limit as the number of particles and the time window go to infinity but the graph remains finite, the large-deviation rate…

Statistical Mechanics · Physics 2020-12-02 Davide Gabrielli , D. R. Michiel Renger

For biased random walk on the infinite cluster in supercritical i.i.d.\ percolation on $\Z^2$, where the bias of the walk is quantified by a parameter $\beta>1$, it has been conjectured (and partly proved) that there exists a critical value…

Probability · Mathematics 2010-12-16 Maria Deijfen , Olle Häggström

We study a continuous time random walk on the $d$-dimensional lattice, subject to a drift and an attraction to large clusters of a subcritical Bernoulli site percolation. We find two distinct regimes: a ballistic one, and a subballistic one…

Probability · Mathematics 2007-10-12 Francis Comets , Francois Simenhaus

We consider the one-dimensional partially asymmetric exclusion process with random hopping rates, in which a fraction of particles (or sites) have a preferential jumping direction against the global drift. In this case the accumulated…

Disordered Systems and Neural Networks · Physics 2009-11-10 R. Juhasz , L. Santen , F. Igloi

We consider biased random walks on random networks constituted by a random comb comprising a backbone with quenched-disordered random-length branches. The backbone and the branches run in the direction of the bias. For the bare model as…

Statistical Mechanics · Physics 2025-06-09 Mrinal Sarkar , Shamik Gupta

We study the continuous absorbing-state phase transition in the one-dimensional diffusive epidemic process via mean-field theory and Monte Carlo simulation. In this model, particles of two species (A and B) hop on a lattice and undergo…

Statistical Mechanics · Physics 2009-11-11 Daniel Souza Maia , Ronald Dickman

Percolation transition is widely observed in networks ranging from biology to engineering. While much attention has been paid to network topologies, studies rarely focus on critical percolation phenomena driven by network dynamics. Using…

Physics and Society · Physics 2019-01-08 Guanwen Zeng , Daqing Li , Shengmin Guo , Liang Gao , Ziyou Gao , H. Eugene Stanley , Shlomo Havlin

Drift diffusion models (DDMs) have found widespread use in computational neuroscience and other fields. They model evidence accumulation in simple decision tasks as a stochastic process drifting towards a decision barrier. In models where…

Methodology · Statistics 2025-12-12 Sicheng Liu , Alexander Fengler , Michael J. Frank , Matthew T. Harrison