论文标题
自主系统中的能量和信息流
Energy and information flows in autonomous systems
论文作者
论文摘要
多组分分子机在生物学上无处不在。我们回顾了使用自主二分马匹动力学描述其热力学特性的最新进展。第一和第二定律可以分为适用于两个组件系统每个子系统的本地版本，这说明一个人不仅可以解决子系统之间的能量流，而且还可以量化每个子系统动态如何影响关节系统的熵平衡。将框架应用于分子尺度传感器，可以使其能量需求更紧密。可以从统一的角度量化两个组件耦合的机器通过传输功率或像信息引擎一样在何种程度上进行量化研究，通过产生信息流以将热波动纠正为输出功率。
Multi-component molecular machines are ubiquitous in biology. We review recent progress on describing their thermodynamic properties using autonomous bipartite Markovian dynamics. The first and second laws can be split into local versions applicable to each subsystem of a two-component system, illustrating that one can not only resolve energy flows between the subsystems but also information flows quantifying how each subsystem's dynamics influence the joint system's entropy balance. Applying the framework to molecular-scale sensors allows one to derive tighter bounds on their energy requirement. Two-component strongly coupled machines can be studied from a unifying perspective quantifying to what extent they operate conventionally by transducing power or like an information engine by generating information flow to rectify thermal fluctuations into output power.
