ArticleProceedings of the National Academy of Sciences of the United States of America2024
Is stochastic thermodynamics the key to understanding the energy costs of computation?
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Instability-driven electrohydrodynamic neurons for probabilistic computing.Nature communications · 2026Article
- Stochastic thermodynamics of social imitation beyond energetics.Nature communications · 2026Article
- Identification and quantification of irreversibility in stochastic systems.Physical chemistry chemical physics : PCCP · 2026Review
- Entropy production bounds for systems running computer programs.PNAS nexus · 2026Article
- Liquid-in-Liquid Prints: High-Density Biochemically Encoded Information Preserved in Microdroplet Arrays.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Integrating the Contrasting Perspectives Between the Constrained Disorder Principle and Deterministic Optical Nanoscopy: Enhancing Information Extraction from Imaging of Complex Systems.Bioengineering (Basel, Switzerland) · 2026Article
- Nonlinear thermodynamic computing out of equilibrium.Nature communications · 2026Article
- State-space kinetic Ising model reveals task-dependent entropy flow in sparsely active nonequilibrium neuronal dynamics.Nature communications · 2025Article
- Experimentally achieving minimal dissipation via thermodynamically optimal transport.Nature communications · 2025Article
- Landauer's Principle: Past, Present and Future.Entropy (Basel, Switzerland) · 2025Article
- Maximizing Free Energy Gain.Entropy (Basel, Switzerland) · 2025Article
- Modeling the Arrows of Time with Causal Multibaker Maps.Entropy (Basel, Switzerland) · 2024Article
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19 authors.
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Abstract
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.
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