Bulletin of the American Physical Society
APS March Meeting 2020
Volume 65, Number 1
Monday–Friday, March 2–6, 2020; Denver, Colorado
Session A25: Thermodynamics of Biological and Artificial Computation
8:00 AM–10:12 AM,
Monday, March 2, 2020
Room: 402
Sponsoring
Units:
GSNP DCOMP
Chair: David Wolpert, Santa Fe Inst
Abstract: A25.00008 : Trajectory-Class Fluctuation Theorems: Work Decomposition in Metastable Information Processing
Presenter:
Greg Wimsatt
(University of California, Davis)
Authors:
Greg Wimsatt
(University of California, Davis)
Olli Saira
(California Institute of Technology)
Alec Boyd
(University of California, Davis)
Matthew Matheny
(California Institute of Technology)
Siyuan Han
(University of Kansas)
Michael Roukes
(California Institute of Technology)
James P Crutchfield
(University of California, Davis)
The full work distribution generated during thermodynamic computing is surprisingly complex. Even if simple, efficient, and accurate, the effective information processing may exhibit thermodynamically-distinct temporal substages. For example, a bit erasure protocol similar to that of Jun et. al. (2014 PRL 113.190601) consists of four substages, each linearly changing a single protocol parameter. Combining substage decomposition with partitioning the microscopic state-space into thermodynamically-metastable regions, a symbolic dynamics emerges that naturally decomposes the work distribution into canonical components, with each substage obeying its own fluctuation theorems. Practically, through describing macroscopic observables, such as net work, these components can be used to diagnose the predominance of specific microscopic informational failure and success modes. In this way, the trajectory-class fluctuation theorems can be used to guide optimal protocol design.
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