Is stochastic thermodynamics the key to understanding the energy costs of computation?

• 成果类型: Article
• 署名作者: Wolpert, David H.; Korbel, Jan; Lynn, Christopher W.; Tasnim, Farita; Grochow, Joshua A.; Kardes, Gulce; Aimone, James B.; Balasubramanian, Vijay; De Giuli, Eric; Doty, David; Freitas, Nahuel; Marsili, Matteo; Ouldridge, Thomas E.; Richa, Andrea W.; Riechers, Paul; Roldan, Edgar; Rubenstein, Brenda; Toroczkai, Zoltan; Paradiso, Joseph
• 署名单位: The Santa Fe Institute; Arizona State University; Arizona State University-Tempe; Abdus Salam International Centre for Theoretical Physics (ICTP); Yeshiva University; Medical University of Vienna; Princeton University; City University of New York (CUNY) System; Yale University; City University of New York (CUNY) System; University of Colorado System; University of Colorado Boulder; United States Department of Energy (DOE); Sandia National Laboratories; University of Pennsylvania; University of Oxford; Toronto Metropolitan University; University of California System; University of California Davis; University of Buenos Aires; Imperial College London; Imperial College London; Nanyang Technological University; Brown University; University of Notre Dame; Massachusetts Institute of Technology (MIT)
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-14620
• DOI: 10.1073/pnas.2321112121
• 发表日期: 2024-11-05
• 关键词: fluctuation theorem; jarzynski equality; physics; verification; INFORMATION; complexity; entropy

摘要

The relationship between the thermodynamic and computational properties of physical systems has been a major theoretical interest since at least the 19th century. It has also become of increasing practical importance over the last half-century as the energetic cost of digital devices has exploded. Importantly, real-world computers obey multiple physical constraints on how they work, which affects their thermodynamic properties. Moreover, many of these constraints apply to both naturally occurring computers, like brains or Eukaryotic cells, and digital systems. Most obviously, all such systems must finish their computation quickly, using as few degrees of freedom as possible. This means that they operate far from thermal equilibrium. Furthermore, many computers, both digital and biological, are modular, hierarchical systems with strong constraints on the connectivity among their subsystems. Yet another example is that to simplify their design, digital computers are required to be periodic processes governed by a global clock. None of these constraints were considered in 20th-century analyses of the thermodynamics of computation. The new field of stochastic thermodynamics provides formal tools for analyzing systems subject to all of these constraints. We argue here that these tools may help us understand at a far deeper level just how the fundamental thermodynamic properties of physical systems are related to the computation they perform.