Machine learning active-nematic hydrodynamics
Machine learning active-nematic hydrodynamics
About this item
Full title
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Publisher
United States: National Academy of Sciences
Journal title
Language
English
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Publication information
Publisher
United States: National Academy of Sciences
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Scope and Contents
Contents
Hydrodynamic theories effectively describe many-body systems out of equilibrium in terms of a few macroscopic parameters. However, such parameters are difficult to determine from microscopic information. Seldom is this challenge more apparent than in active matter, where the hydrodynamic parameters are in fact fields that encode the distribution of...
Alternative Titles
Full title
Machine learning active-nematic hydrodynamics
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7958379
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7958379
Other Identifiers
ISSN
0027-8424
E-ISSN
1091-6490
DOI
10.1073/pnas.2016708118
