Effective Affinity for Generic Currents in Markov Processes
Adarsh Raghu, Izaak Neri

TL;DR
This paper introduces the concept of effective affinity for generic currents in Markov processes, capturing dissipative and fluctuation properties, and relates it to stalling forces in biological motor models.
Contribution
It defines an effective affinity applicable to multiple coupled currents, extending thermodynamic concepts beyond uncoupled systems, with theoretical and biological implications.
Findings
Effective affinity determines current direction.
It bounds dissipation rates and constrains fluctuations.
In certain models, effective affinity equals stalling force.
Abstract
In nonequilibrium systems with uncoupled currents, the thermodynamic affinity determines the direction of currents, quantifies dissipation, and constrains current fluctuations. However, these properties of the thermodynamic affinity do not hold in complex systems with multiple coupled currents. For this reason, there has been an ongoing search in nonequilibrium thermodynamics for an affinity-like quantity, known as the effective affinity, which applies to a single current in a system with multiple coupled currents. Here, we introduce an effective affinity that applies to generic currents in time-homogeneous Markov processes. We show that the effective affinity is a single number encapsulating several dissipative and fluctuation properties of fluctuating currents: the effective affinity determines the direction of flow of the current; the effective affinity multiplied by the current is a…
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Taxonomy
TopicsAdvanced Thermodynamics and Statistical Mechanics · Complex Systems and Time Series Analysis · Phase Equilibria and Thermodynamics
