First and Second Laws of Information Processing by Nonequilibrium Dynamical States

TL;DR

This paper establishes a theoretical framework linking nonequilibrium thermodynamics to information processing, deriving a First Law that refines the Second Laws and analyzing an information ratchet to show how nonequilibrium states affect work extraction.

Contribution

It introduces a unified First Law of information processing for nonequilibrium steady states, extending traditional Second Laws with strict equalities and analyzing their implications.

Findings

Decomposition of surprisal leads to a First Law extending Second Laws.

Application of fluctuation theorems shows reduction to Second Laws in certain limits.

Analysis of an autonomous Maxwellian ratchet reveals effects of nonequilibrium states on information engines.

Abstract

The averaged steady-state surprisal links a driven stochastic system's information processing to its nonequilibrium thermodynamic response. By explicitly accounting for the effects of nonequilibrium steady states, a decomposition of the surprisal results in an information processing First Law that extends and tightens -- to strict equalities -- various information processing Second Laws. Applying stochastic thermodynamics' integral fluctuation theorems then shows that the decomposition reduces to the second laws under appropriate limits. In unifying them, the First Law paves the way to identifying the mechanisms by which nonequilibrium steady-state systems extract work from information-bearing degrees of freedom. To illustrate, we analyze an autonomous Maxwellian information ratchet that tunably violates detailed balance in its effective dynamics. This demonstrates how the presence of nonequilibrium steady states qualitatively alters an information engine's allowed functionality.