English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper we focus on the development of new methods suitable forefficient and reliable coarse-graining of {\it non-equilibrium} molecularsystems. In this context, we propose error estimation and controlled-fidelitymodel reduction methods based on Path-Space Information Theory, and combine itwith statistical parametric estimation of rates for non-equilibrium stationaryprocesses. The approach we propose extends the applicability of existinginformation-based methods for deriving parametrized coarse-grained models toNon-Equilibrium systems with Stationary States (NESS). In the context ofcoarse-graining it allows for constructing optimal parametrized Markoviancoarse-grained dynamics, by minimizing information loss (due tocoarse-graining) on the path space. Furthermore, the associated path-spaceFisher Information Matrix can provide confidence intervals for thecorresponding parameter estimators. We demonstrate the proposed coarse-grainingmethod in a non-equilibrium system with diffusing interacting particles, drivenby out-of-equilibrium boundary conditions.

Information-theoretic tools for parametrized coarse-graining of non-equilibrium extended systems