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We investigate the observables of the one-dimensional model for anomalous transport in semiconductor devices where diffusion arises from scattering at dislocations at fixed random positions, known as L\'evy-Lorentz gas. To gain insight into…

Statistical Mechanics · Physics 2024-08-15 Muhammad Tayyab

The Slicer Map is a one-dimensional non-chaotic dynamical system that shows sub-, super-, and normal diffusion as a function of its control parameter. In a recent paper [Salari et al., CHAOS 25, 073113 (2015)] it was found that the moments…

Statistical Mechanics · Physics 2019-06-11 Claudio Giberti , Lamberto Rondoni , Muhammad Tayyab , Juergen Vollmer

Since groundbreaking works in the 1980s it is well-known that simple deterministic dynamical systems can display intermittent dynamics and weak chaos leading to anomalous diffusion. A paradigmatic example is the Pomeau-Manneville (PM) map…

Chaotic Dynamics · Physics 2025-01-30 Samuel Brevitt , Alexander Schulz , Dominic Pegler , Holger Kantz , Rainer Klages

Tracer diffusion in single-file systems, where particles are restricted to move on a line without passing each other, has been a fertile ground to investigate anomalous diffusion and strong memory effects. While the long-time behavior of…

Statistical Mechanics · Physics 2025-05-28 Alexis Poncet , Aurélien Grabsch , Olivier Bénichou

The Supercritical Fluid (SCF) is known to exhibit salient dynamic and thermodynamic crossovers and inhomogeneous molecular distribution. But the question as to what basic physics underlies these microscopic and macroscopic anomalies remains…

Soft Condensed Matter · Physics 2020-01-01 Min Young Ha , Tae Jun Yoon , Tsvi Tlusty , YongSeok Jho , Won Bo Lee

Diffusion maps approximate the generator of Langevin dynamics from simulation data. They afford a means of identifying the slowly-evolving principal modes of high-dimensional molecular systems. When combined with a biasing mechanism,…

Data Analysis, Statistics and Probability · Physics 2020-07-01 Zofia Trstanova , Ben Leimkuhler , Tony Lelièvre

Strong anomalous diffusion is characterized by asymptotic power-law growth of the moments of displacement, with exponents that do not depend linearly on the order of the moment. The exponents concerning small-order moments are dominated by…

Statistical Mechanics · Physics 2021-01-27 Jürgen Vollmer , Lamberto Rondoni , Muhammad Tayyab , Claudio Giberti , Carlos Mejía-Monasterio

We examine characteristic properties of deterministic and stochastic diffusion in low-dimensional chaotic dynamical systems. As an example, we consider a periodic array of scatterers defined by a simple chaotic map on the line. Adding…

Chaotic Dynamics · Physics 2009-11-07 R. Klages

We analyze the dynamics of streaming stochastic gradient descent (SGD) in the high-dimensional limit when applied to generalized linear models and multi-index models (e.g. logistic regression, phase retrieval) with general data-covariance.…

Optimization and Control · Mathematics 2023-08-21 Elizabeth Collins-Woodfin , Courtney Paquette , Elliot Paquette , Inbar Seroussi

In this work we propose a two-dimensional extension of a previously defined one-dimensional version of a model of counterflowing particles, which considers an adapted Fermi-Dirac distribution to describe the transition probabilities. In…

Soft Condensed Matter · Physics 2020-09-02 E. V. Stock , R. da Silva

A central problem in data analysis is the low dimensional representation of high dimensional data, and the concise description of its underlying geometry and density. In the analysis of large scale simulations of complex dynamical systems,…

Numerical Analysis · Mathematics 2007-05-23 Boaz Nadler , Stephane Lafon , Ronald R. Coifman , Ioannis G. Kevrekidis

We explore the dynamics of a tracer in an active particle harmonic chain, investigating the influence of interactions. Our analysis involves calculating mean-squared displacements (MSD) and space-time correlations through Green's function…

Statistical Mechanics · Physics 2026-04-07 Subhajit Paul , Abhishek Dhar , Debasish Chaudhuri

Continuous time random walks and Langevin equations are two classes of stochastic models for describing the dynamics of particles in the natural world. While some of the processes can be conveniently characterized by both of them, more…

Statistical Mechanics · Physics 2019-01-28 Xudong Wang , Yao Chen , Weihua Deng

Lagrangian particle methods based on detailed atomic and molecular models are powerful computational tools for studying the dynamics of microscale and nanoscale systems. However, the maximum time step is limited by the smallest oscillation…

Computational Physics · Physics 2019-06-26 Ansel L. Blumers , Zhen Li , George Em Karniadakis

In this paper, we proposed a stochastic model which describes two species of particles moving in counterflow. The model generalizes the theoretical framework describing the transport in random systems since particles can work as mobile…

Soft Condensed Matter · Physics 2017-08-09 Eduardo Velasco Stock , Roberto da Silva , Henrique Almeida Fernandes

In this paper, we study the statistical evolution of the large-scale structure (LSS), focusing on the joint probability distribution function (PDF) of the coarse-grained cosmic field and its role in constructing effective dynamics. As the…

Cosmology and Nongalactic Astrophysics · Physics 2021-10-20 Xin Wang

We study a stochastic lattice gas of particles undergoing asymmetric diffusion in two dimensions. Transitions between a low-density uniform phase and high-density non-uniform phases characterized by localized or extended structure are…

Condensed Matter · Physics 2009-10-22 Kwan-tai Leung

Inspired by problems in biochemical kinetics, we study statistical properties of an overdamped Langevin process whose friction coefficient depends on the state of a similar, unobserved process. Integrating out the latter, we derive the long…

Statistical Mechanics · Physics 2009-08-13 Golan Bel , Ilya Nemenman

We study various temporal correlation functions of a tagged particle in one-dimensional systems of interacting point particles evolving with Hamiltonian dynamics. Initial conditions of the particles are chosen from the canonical thermal…

Statistical Mechanics · Physics 2015-06-25 Anjan Roy , Abhishek Dhar , Onuttom Narayan , Sanjib Sabhapandit

Cellular differentiation is governed by gene regulatory networks, the high-dimensional stochastic biochemical systems that determine the transcriptional landscape and mediate cellular responses to signals and perturbations. Although…

Molecular Networks · Quantitative Biology 2026-04-29 Suryanarayana Maddu , Victor Chardès , Michael J. Shelley
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