Landi Gabriel T
Instituto de Física, Universidade de São Paulo, São Paulo 05314-970, Brazil.
School of Physics, Trinity College Dublin, College Green, 2 Dublin, Ireland.
Entropy (Basel). 2021 Dec 2;23(12):1627. doi: 10.3390/e23121627.
We constructed a collision model where measurements in the system, together with a Bayesian decision rule, are used to classify the incoming ancillas as having either high or low ergotropy (maximum extractable work). The former are allowed to leave, while the latter are redirected for further processing, aimed at increasing their ergotropy further. The ancillas play the role of a quantum battery, and the collision model, therefore, implements a Maxwell demon. To make the process autonomous and with a well-defined limit cycle, the information collected by the demon is reset after each collision by means of a cold heat bath.
我们构建了一个碰撞模型，其中系统中的测量结果与贝叶斯决策规则一起用于将传入的辅助量子比特分类为具有高或低的量子熵（最大可提取功）。前者被允许离开，而后者被重新定向进行进一步处理，目的是进一步提高其量子熵。辅助量子比特起到量子电池的作用，因此，碰撞模型实现了一个麦克斯韦妖。为了使过程自主且具有明确的极限环，妖收集的信息在每次碰撞后通过冷热库进行重置。
