Control Strategies for Maintaining Transport Symmetries Far From Equilibrium
David Andrieux
TL;DR
The paper introduces two dynamical equivalence-class strategies, $e$ and $m$, to steer transport in mesoscopic Markov devices while preserving symmetry properties far from equilibrium. The $e$-scheme uses an affinity-based representation, yielding anti-symmetric current–affinity relations and a KL-based potential that minimizes distortion relative to the original dynamics. The $m$-scheme builds on a current-based representation, producing linearly parameterized dynamics with symmetric nonlinear response, and a distinct equivalence class that preserves activities. Together, these schemes reveal hidden geometric structures in parameter space and offer practical routes to design and control coupled transport processes in molecular machines and membrane transport, with explicit constructions for representative models. The frameworks bridge information geometry, fluctuation theory, and nonequilibrium thermodynamics, enabling targeted output control under strong driving.
Abstract
We present two strategies for controlling the transport dynamics of mesoscopic devices. In both cases, we manipulate the system's output - such as particle currents and energy flows - while maintaining symmetric transport properties, even under far-from-equilibrium conditions. We provide exact descriptions of each scheme and investigate their characteristics. Notably, one of them minimizes the dissimilarity between the original and modified processes, as quantified by the Kullback-Leibler divergence. These findings can be used to improve the design and control of mesoscopic systems.
