Stochastic cycle selection in active flow networks
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8200.full.pdf
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1.1 MB
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Author(s)
Woodhouse, Francis G.
Fawcett, Joanna B.
Forrow, Aden
Dunkel, Joern
Date Issued
July 2016
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Woodhouse, Francis G. et al. “Stochastic Cycle Selection in Active Flow Networks.” Proceedings of the National Academy of Sciences 113, 29 (July 2016): 8200–8205 © 2016 National Academy of Sciences
Version
Final published version
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. Keywords: networks; active transport; stochastic dynamics; topology
MIT Department
Massachusetts Institute of Technology. Department of Mathematics
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1073/PNAS.1603351113
