Journal
NEW JOURNAL OF PHYSICS
Volume 21, Issue 6, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/1367-2630/ab2484
Keywords
thermodynamics of information; biomolecular systems; statistical mechanics; molecular computation
Categories
Funding
- Royal Society University Research Fellowship
- Imperial College London AMMP studentship
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By designing and leveraging an explicit molecular realisation of a measurement-and-feedback-powered Szilard engine, we investigate the extraction of work from complex environments by minimal machines with finite capacity for memory and decision-making. Living systems perform inference to exploit complex structure, or correlations, in their environment, but the physical limits and underlying cost/benefit trade-offs involved in doing so remain unclear. To probe these questions, we consider a minimal model for a structured environment-a correlated sequence of molecules- and explore mechanisms based on extended Szilard engines for extracting the work stored in these non-equilibrium correlations. We consider systems limited to a single bit of memory making binary 'choices' at each step. We demonstrate that increasingly complex environments allow increasingly sophisticated inference strategies to extract more free energy than simpler alternatives, and argue that optimal design of such machines should also consider the free energy reserves required to ensure robustness against fluctuations due to mistakes.
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