Complexity Sciences Center and Physics Department, University of California at Davis, One Shields Avenue, Davis, California 95616, USA.
Department of Physics, University of California, Berkeley, California 94720, USA.
Phys Rev E. 2017 Jan;95(1-1):012152. doi: 10.1103/PhysRevE.95.012152. Epub 2017 Jan 26.
Information engines can use structured environments as a resource to generate work by randomizing ordered inputs and leveraging the increased Shannon entropy to transfer energy from a thermal reservoir to a work reservoir. We give a broadly applicable expression for the work production of an information engine, generally modeled as a memoryful channel that communicates inputs to outputs as it interacts with an evolving environment. The expression establishes that an information engine must have more than one memory state in order to leverage input environment correlations. To emphasize this functioning, we designed an information engine powered solely by temporal correlations and not by statistical biases, as employed by previous engines. Key to this is the engine's ability to synchronize-the engine automatically returns to a desired dynamical phase when thrown into an unwanted, dissipative phase by corruptions in the input-that is, by unanticipated environmental fluctuations. This self-correcting mechanism is robust up to a critical level of corruption, beyond which the system fails to act as an engine. We give explicit analytical expressions for both work and critical corruption level and summarize engine performance via a thermodynamic-function phase diagram over engine control parameters. The results reveal a thermodynamic mechanism based on nonergodicity that underlies error correction as it operates to support resilient engineered and biological systems.
信息引擎可以将结构化环境作为资源，通过随机化有序输入并利用增加的香农熵将能量从热库转移到工作库来生成工作。我们为信息引擎的工作产生提供了一个广泛适用的表达式，通常将其建模为一个具有记忆功能的通道，在与不断发展的环境相互作用时，将输入传递到输出。该表达式表明，为了利用输入环境的相关性，信息引擎必须具有多个记忆状态。为了强调这种功能，我们设计了一种信息引擎，它仅由时间相关性驱动，而不是由以前的引擎所采用的统计偏差驱动。关键是引擎的同步能力——当输入受到损坏而进入不需要的耗散状态时，引擎会自动返回到所需的动态相位，也就是说，当环境出现意外波动时，引擎会自动返回到所需的动态相位。这种自我纠正机制在达到临界损坏水平之前是稳健的，超过该水平后，系统将无法作为引擎运行。我们给出了工作和临界损坏水平的明确解析表达式，并通过信息引擎控制参数的热力学函数相图总结了引擎的性能。结果揭示了一种基于非遍历性的热力学机制，它在运行时作为错误校正的基础，以支持有弹性的工程和生物系统。
