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We construct a collision model where measurements in the system, togetherwith a Bayesian decision rule, are used to classify the incoming ancillas ashaving either high or low ergotropy (maximum extractable work). The former areallowed to leave, while the latter are redirected for further processing, aimedat increasing their ergotropy further. The ancillas play the role of a quantumbattery, and the collision model therefore implements a Maxwell demon. To makethe process autonomous, and with a well defined limit cycle, the informationcollected by the demon is reset after each collision by means of a cold heatbath.

Battery charging in collision models with Bayesian risk strategies