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Stochastic cycle selection in active flow networks.

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Woodhouse, Francis Gordon  ORCID logo  https://orcid.org/0000-0002-5305-5510
Forrow, Aden 
Fawcett, Joanna B 
Dunkel, Jörn 

Abstract

Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models.

Description

Keywords

active transport, networks, stochastic dynamics, topology, Models, Theoretical, Physical Phenomena, Stochastic Processes

Journal Title

Proc Natl Acad Sci U S A

Conference Name

Journal ISSN

0027-8424
1091-6490

Volume Title

Publisher

Proceedings of the National Academy of Sciences