Information transmission and signal permutation in active flow networks
Name
Woodhouse_2018_New_J._Phys._20_035003.pdf
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830.26 KB
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Adobe PDF
Checksum (MD5)
ab2afa4ea5c2c9b2f33fa074037b9531
Author(s)
Woodhouse, Francis G
Fawcett, Joanna B
Dunkel, Joern
Date Issued
October 2017
Journal
New Journal of Physics
Publisher
IOP Publishing
Citation
Woodhouse, Francis G et al. “Information Transmission and Signal Permutation in Active Flow Networks.” New Journal of Physics 20, 3 (March 2018): 03500 © 2018 The Author(s)
Version
Final published version
Abstract
Recent experiments show that both natural and artificial microswimmers in narrow channel-like geometries will self-organise to form steady, directed flows. This suggests that networks of flowing active matter could function as novel autonomous microfluidic devices. However, little is known about how information propagates through these far-from-equilibrium systems. Through a mathematical analogy with spin-ice vertex models, we inves tigate here the input-output characteristics of generic incompressible active flow networks (AFNs). Our analysis shows that information transport through an AFN is inherently different from conventional pressure or voltage driven networks. Active flows on hexagonal arrays preserve input information over longer distances than their passive counterparts and are highly sensitive to bulk topological defects, whose presence can be inferred from marginal input-output distributions alone. This sensitivity further allows controlled permutations on parallel inputs, revealing an unexpected link between active matter and group theory that can guide new microfluidic mixing strategies facilitated by active matter and aid the design of generic autonomous information transport networks.
MIT Department
Massachusetts Institute of Technology. Department of Mathematics
Terms of Use
Creative Commons Attribution 3.0 Unported license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1088/1367-2630/aab680
