Information-to-work conversion in single molecule experiments: from discrete to continuous feedback

TL;DR

This paper explores the theoretical limits of work extraction in single molecule experiments with feedback, providing a comprehensive model that bridges discrete and continuous feedback regimes and aligns with experimental DNA hairpin data.

Contribution

It introduces a full work distribution model for feedback-controlled single molecule experiments, unifying discrete and continuous feedback, with analytical expressions and experimental relevance.

Findings

Derived a detailed fluctuation theorem incorporating feedback information.

Provided analytical bounds on average work extraction, tight in the continuous feedback limit.

Validated the model with Monte Carlo simulations of DNA hairpin dynamics.

Abstract

We theoretically investigate the extractable work in single molecule unfolding-folding experiments with applied feedback. Using a simple two-state model, we obtain a description of the full work distribution, from discrete to continuous feedback. The effect of the feedback is captured by a detailed fluctuation theorem, accounting for the information aquired. We find analytical expressions for the average work extraction as well as an experimentally measurable bound thereof, which becomes tight in the continuous feedback limit. We further determine the parameters for maximal power, or rate of work extraction. While our two-state model only depends on a single, effective transition rate, we find quantitative agreement with Monte Carlo simulations of DNA hairpin unfolding-folding dynamics.