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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A framework is proposed to generate a phenomenological model that extractsthe essence of a dynamical system (DS) with large degrees of freedom usingmachine learning. For a given microscopic DS, the optimum transformation to asmall number of macroscopic variables, which is expected to be extensive, andthe rule of time evolution that the variables obey are simultaneouslyidentified. The utility of this method is demonstrated through its applicationto the nonequilibrium relaxation of the three-state Potts model.

Dimensional Reduction of Dynamical Systems by Machine Learning: Automatic Generation of the Optimum Extensive Variables and Their Time-Evolution Map