Information and maximum power in a feedback controlled Brownian ratchet

TL;DR

This paper analyzes feedback-controlled Brownian ratchets, deriving analytical expressions for power output and revealing upper bounds proportional to the information used in control, highlighting the role of information in optimizing these systems.

Contribution

It provides analytical formulas for power in feedback ratchets and establishes bounds linking power output to the amount of information utilized.

Findings

Maximum power output is bounded and proportional to the information.

Changing from open-loop to feedback control increases power within a linear bound.

Analytical expressions are derived for one-particle and few-particle ratchets.

Abstract

Closed-loop or feedback controlled ratchets are Brownian motors that operate using information about the state of the system. For these ratchets, we compute the power output and we investigate its relation with the information used in the feedback control. We get analytical expressions for one-particle and few-particle flashing ratchets, and we find that the maximum power output has an upper bound proportional to the information. In addition, we show that the increase of the power output that results from changing the optimal open-loop ratchet to a closed-loop ratchet also has an upper bound that is linear in the information.