自治信息引擎中的快速高性能函数化
Fast Functionalization with High Performance in the Autonomous Information Engine
摘要：
Mandal和Jarzynski提出了一个完全自主的信息热机，由一个恶魔，一个质量和一个记忆寄存器与热库相互作用。该器件通过将信息写入存储器寄存器将热能转换为机械功，或者相反，通过消耗机械功来擦除信息。在这里，我们得到了一个速度限制不等式之间的弛豫时间的状态转换和初始和最终分布之间的距离，其中的动力学活动和熵产生的组合起着重要的作用。这样的不等式提供了一个暗示，速度性能之间的权衡关系存在的弛豫时间功能状态和平均产量。为了获得快速的功能化，同时保持性能，我们表明，信息热机的松弛动力学可以通过设计一个最佳的初始状态的恶魔显着加速。我们的设计原理受到所谓的Mpemba效应的启发，即水在最初加热时冻结得更快。
英文摘要：
Mandal and Jarzynski have proposed a fully autonomous information heat engine, consisting of a demon, a mass and a memory register interacting with a thermal reservoir. This device converts thermal energy into mechanical work by writing information to a memory register, or conversely, erasing information by consuming mechanical work. Here, we derive a speed limit inequality between the relaxation time of state transformation and the distance between the initial and final distributions, where the combination of the dynamical activity and entropy production plays an important role. Such inequality provides a hint that a speed-performance trade-off relation exists between the relaxation time to functional state and the average production. To obtain fast functionalization while maintaining the performance, we show that the relaxation dynamics of information heat engine can be accelerated significantly by devising an optimal initial state of the demon. Our design principle is inspired by the so-called Mpemba effect, where water freezes faster when initially heated.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
