Multiple-scale stochastic processes: decimation, averaging and beyond

TL;DR

This paper develops asymptotic methods for modeling multi-scale stochastic systems, focusing on decimation, averaging, and the treatment of trajectory functionals, with applications in physics, biology, and chemistry.

Contribution

It introduces new asymptotic techniques for eliminating fast variables and handling functionals of stochastic trajectories, extending homogenization methods in multi-scale stochastic modeling.

Findings

Effective decimation and coarse-graining procedures for stochastic systems.

Homogenization techniques for trajectory functionals like entropy production.

Applications to thermodynamics of small systems and information theory.

Abstract

The recent experimental progresses in handling microscopic systems have allowed to probe them at levels where fluctuations are prominent, calling for stochastic modeling in a large number of physical, chemical and biological phenomena. This has provided fruitful applications for established stochastic methods and motivated further developments. These systems often involve processes taking place on widely separated time scales. For an efficient modeling one usually focuses on the slower degrees of freedom and it is of great importance to accurately eliminate the fast variables in a controlled fashion, carefully accounting for their net effect on the slower dynamics. This procedure in general requires to perform two different operations: decimation and coarse-graining. We introduce the asymptotic methods that form the basis of this procedure and discuss their application to a series of physical, biological and chemical examples. We then turn our attention to functionals of the stochastic trajectories such as residence times, counting statistics, fluxes, entropy production, etc. which have been increasingly studied in recent years. For such functionals, the elimination of the fast degrees of freedom can present additional difficulties and naive procedures can lead to blatantly inconsistent results. Homogenization techniques for functionals are less covered in the literature and we will pedagogically present them here, as natural extensions of the ones employed for the trajectories. We will also discuss recent applications of these techniques to the thermodynamics of small systems and their interpretation in terms of information-theoretic concepts.