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Active Brownian particles

2012/02/11 by Paweł Romańczuk, Pawel Romanczuk, Markus Bär +4 · 1,141 citations
Environmental Science · Physics and Astronomy · #Active matter #Advanced Thermodynamics and Statistical Mechanics #Biological system #Biology #Brownian motion #Classical mechanics #Diffusion #Dynamics (music) #Ecosystem dynamics and resilience #Mechanics #Micro and Nano Robotics #Nonlinear system #Observable #Pattern formation #Physics #Simple (philosophy) #Statistical physics #Stochastic differential equation #Thermodynamics #cond-mat.other #cond-mat.soft #physics.bio-ph

paper · pdf · doi:10.1140/epjst/e2012-01529-y

published in The European Physical Journal Special Topics 202(1), 1-162 (Springer Science+Business Media) · 161 pages, Review, Eur Phys J Special-Topics, accepted

arxiv created 2012/02/11 · openalex publication_date 2012/03/01 · arxiv updated 2015/06/04 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/06

Abstract

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.

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