Seifert derived an exact fluctuation relation for diffusion processes using the concept of "stochastic system entropy". In this note we extend his formalism to entropic transport. We introduce the notion of relative stochastic entropy, or "relative surprisal", and use it to generalize Seifert's system/medium decomposition of the total entropy. This result allows to apply the concepts of stochastic thermodynamics to diffusion processes in confined geometries, such as ion channels, cellular pores or nanoporous materials. It can be seen as the equivalent for diffusion processes of Esposito and Schaller's generalized fluctuation theorem for "Maxwell demon feedbacks"
Entropy and the fluctuation-dissipation theorem are at the heart of statistical mechan-ics near equi...
A stochastic process is an essential tool for the investigation of the physical and life sciences at...
Physical and chemical stochastic processes described by the master equation are investi-gated. The s...
Seifert derived an exact fluctuation relation for diffusion processes using the concept of "stochast...
Computing the stochastic entropy production associated with the evolution of a stochastic dynamical ...
We analyze Furth's 1933 classical uncertainty relations in the modern language of stochastic differe...
A positive rate of entropy production at steady state is a distinctive feature of truly non-equilibr...
Fluctuation theorem for entropy production is revisited in the framework of stochastic processes. Th...
Diffusion-a measure of dynamics, and entropy-a measure of disorder in the system are found to be int...
Small systems in a thermodynamic medium — like colloids in a suspension or the molec-ular machinery ...
International audienceThe dissipation of general convex entropies for continuous time Markov process...
We consider the optimization of the average entropy production in inhomogeneous temperature environm...
Diffusive transport in porous media is analysed herein as a stochastic process by means of a formali...
Given a probability measure, we consider the diffusion flows of probability measures associated with...
Entropy and the fluctuation-dissipation theorem are at the heart of statistical mechan-ics near equi...
Entropy and the fluctuation-dissipation theorem are at the heart of statistical mechan-ics near equi...
A stochastic process is an essential tool for the investigation of the physical and life sciences at...
Physical and chemical stochastic processes described by the master equation are investi-gated. The s...
Seifert derived an exact fluctuation relation for diffusion processes using the concept of "stochast...
Computing the stochastic entropy production associated with the evolution of a stochastic dynamical ...
We analyze Furth's 1933 classical uncertainty relations in the modern language of stochastic differe...
A positive rate of entropy production at steady state is a distinctive feature of truly non-equilibr...
Fluctuation theorem for entropy production is revisited in the framework of stochastic processes. Th...
Diffusion-a measure of dynamics, and entropy-a measure of disorder in the system are found to be int...
Small systems in a thermodynamic medium — like colloids in a suspension or the molec-ular machinery ...
International audienceThe dissipation of general convex entropies for continuous time Markov process...
We consider the optimization of the average entropy production in inhomogeneous temperature environm...
Diffusive transport in porous media is analysed herein as a stochastic process by means of a formali...
Given a probability measure, we consider the diffusion flows of probability measures associated with...
Entropy and the fluctuation-dissipation theorem are at the heart of statistical mechan-ics near equi...
Entropy and the fluctuation-dissipation theorem are at the heart of statistical mechan-ics near equi...
A stochastic process is an essential tool for the investigation of the physical and life sciences at...
Physical and chemical stochastic processes described by the master equation are investi-gated. The s...