The relationship between the thermodynamic and computational characteristics of dynamical physical systems has been a major theoretical interest since at least the 19th century, and has been of increasing practical importance as the energetic cost of digital devices has exploded over the last half century. One of the most important thermodynamic features of real-world computers is that they operate very far from thermal equilibrium, in finite time, with many quickly (co-)evolving degrees of freedom. Such computers also must almost always obey multiple physical constraints on how they work. For example, all modern digital computers are periodic processes, governed by a global clock. Another example is that many computers are modular, hierarchical systems, with strong restrictions on the connectivity of their subsystems. This properties hold both for naturally occurring computers, like brains or Eukaryotic cells, as well as digital systems. These features of real-world computers are absent in 20th century analyses of the thermodynamics of computational processes, which focused on quasi-statically slow processes. However, the field of stochastic thermodynamics has been developed in the last few decades - and it provides the formal tools for analyzing systems that have exactly these features of real-world computers. We argue here that these tools, together with other tools currently being developed in stochastic thermodynamics, may help us understand at a far deeper level just how the fundamental physical properties of dynamic systems are related to the computation that they perform.

翻译：自19世纪以来，动力学物理系统的热力学特性与计算特性之间的关系一直是理论研究的重大课题。随着过去半个世纪数字设备能耗的激增，这一问题的实际重要性日益凸显。现实世界计算机最重要的热力学特征之一是：它们在远离热平衡的状态下、在有限时间内、以大量快速（共同）演化的自由度运行。此类计算机通常还必须遵守多种物理约束。例如，所有现代数字计算机均为周期性进程，受全局时钟控制；又如，许多计算机是模块化层级系统，其子系统的连接性受到严格限制。这些特性既适用于大脑或真核细胞等天然计算机，也适用于数字系统。20世纪对计算过程热力学的分析主要关注准静态缓慢过程，完全忽略了现实世界计算机的这些特征。然而，近几十年来发展的随机热力学领域——恰好为分析具有现实计算机这些特征的系统提供了形式化工具。我们在此论证：这些工具与随机热力学中正在开发的其他工具相结合，可能有助于我们从更深的层面理解动力学系统的基本物理属性与其所执行计算之间的关联。