论文标题
宏观麦克斯韦的恶魔中的信息流
Information flows in macroscopic Maxwell's demons
论文作者
论文摘要
最近提出了基于CMO的自主麦克斯韦恶魔的实施（物理学修订版129，120602），以证明麦克斯韦恶魔仍然可以在宏观尺度上起作用，只要其电源适当地缩放。在这里，我们首先提供了该模型非自治版本的完整分析表征。然后，我们在通用的自主二分之一的设置中研究系统demon信息流，显示宏观限制。通过这样做，我们可以研究恶魔执行的测量和反馈过程的热力学效率。我们发现，信息流是一个密集的数量，因此，如果所有参数均已固定，则任何麦克斯韦的恶魔都必须停止在有限尺度上工作。但是，可以通过适当缩放热力学力来预防这一点。这些一般结果应用于基于自主的CMOS恶魔。
A CMOS-based implementation of an autonomous Maxwell's demon was recently proposed (Phys. Rev. Lett. 129, 120602) to demonstrate that a Maxwell demon can still work at macroscopic scales, provided that its power supply is scaled appropriately. Here, we first provide a full analytical characterization of the non-autonomous version of that model. We then study system-demon information flows within generic autonomous bipartite setups displaying a macroscopic limit. By doing so, we can study the thermodynamic efficiency of both the measurement and the feedback process performed by the demon. We find that the information flow is an intensive quantity and that, as a consequence, any Maxwell's demon is bound to stop working above a finite scale if all parameters but the scale are fixed. However, this can be prevented by appropriately scaling the thermodynamic forces. These general results are applied to the autonomous CMOS-based demon.
