Information flows in macroscopic Maxwell's demons

TL;DR

This paper analytically characterizes macroscopic Maxwell's demons, exploring information flows and thermodynamic efficiency, revealing scale-dependent limitations and conditions for their sustained operation.

Contribution

It provides a full analytical model of autonomous Maxwell's demons and analyzes their information flow and efficiency at macroscopic scales.

Findings

Information flow is an intensive quantity.

Maxwell's demon stops working above a finite scale unless thermodynamic forces are scaled.

The results are applied to a CMOS-based autonomous demon.

Abstract

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.