Title |
Optimal Control of Transitions between Nonequilibrium Steady States
|
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Published in |
PLOS ONE, December 2013
|
DOI | 10.1371/journal.pone.0082754 |
Pubmed ID | |
Authors |
Patrick R. Zulkowski, David A. Sivak, Michael R. DeWeese |
Abstract |
Biological systems fundamentally exist out of equilibrium in order to preserve organized structures and processes. Many changing cellular conditions can be represented as transitions between nonequilibrium steady states, and organisms have an interest in optimizing such transitions. Using the Hatano-Sasa Y-value, we extend a recently developed geometrical framework for determining optimal protocols so that it can be applied to systems driven from nonequilibrium steady states. We calculate and numerically verify optimal protocols for a colloidal particle dragged through solution by a translating optical trap with two controllable parameters. We offer experimental predictions, specifically that optimal protocols are significantly less costly than naive ones. Optimal protocols similar to these may ultimately point to design principles for biological energy transduction systems and guide the design of artificial molecular machines. |
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Geographical breakdown
Country | Count | As % |
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United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 6 | 10% |
Germany | 2 | 3% |
Brazil | 1 | 2% |
Venezuela, Bolivarian Republic of | 1 | 2% |
Canada | 1 | 2% |
Unknown | 50 | 82% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 17 | 28% |
Researcher | 12 | 20% |
Student > Bachelor | 7 | 11% |
Student > Master | 5 | 8% |
Professor | 4 | 7% |
Other | 9 | 15% |
Unknown | 7 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Physics and Astronomy | 29 | 48% |
Agricultural and Biological Sciences | 10 | 16% |
Mathematics | 3 | 5% |
Biochemistry, Genetics and Molecular Biology | 3 | 5% |
Neuroscience | 3 | 5% |
Other | 5 | 8% |
Unknown | 8 | 13% |