• Open Access

Balancing error and dissipation in computing

Paul M. Riechers, Alexander B. Boyd, Gregory W. Wimsatt, and James P. Crutchfield
Phys. Rev. Research 2, 033524 – Published 30 September 2020
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Abstract

Modern digital electronics support remarkably reliable computing, especially given the challenge of controlling nanoscale logical components that interact in fluctuating environments. However, we demonstrate that the high-reliability limit is subject to a fundamental error–energy-efficiency tradeoff that arises from time-symmetric control: requiring a low probability of error causes energy consumption to diverge as the logarithm of the inverse error rate for nonreciprocal logical transitions. The reciprocity (self-invertibility) of a computation is a stricter condition for thermodynamic efficiency than logical reversibility (invertibility), the latter being the root of Landauer's work bound on erasing information. Beyond engineered computation, the results identify a generic error–dissipation tradeoff in steady-state transformations of genetic information carried out by biological organisms. The lesson is that computational dissipation under time-symmetric control cannot reach, and is often far above, the Landauer limit. In this way, time-asymmetry becomes a design principle for thermodynamically efficient computing.

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  • Received 14 September 2019
  • Accepted 24 August 2020

DOI:https://doi.org/10.1103/PhysRevResearch.2.033524

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied PhysicsNonlinear DynamicsStatistical Physics & ThermodynamicsPhysics of Living Systems

Authors & Affiliations

Paul M. Riechers1,*, Alexander B. Boyd1,†, Gregory W. Wimsatt2,‡, and James P. Crutchfield2,§

  • 1Complexity Institute and School of Physical and Mathematical Sciences, Nanyang Technological University, 637371 Singapore, Singapore
  • 2Complexity Sciences Center and Physics Department, University of California at Davis, One Shields Avenue, Davis, California 95616, USA

  • *pmriechers@gmail.com
  • abboyd@ucdavis.edu
  • gwwimsatt@ucdavis.edu
  • §chaos@ucdavis.edu

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Issue

Vol. 2, Iss. 3 — September - November 2020

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