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

An activity fundamental to science is building mathematical models. Thesemodels are used to both predict the results of future experiments and gaininsight into the structure of the system under study. We present an algorithmthat automates the model building process in a scientifically principled way.The algorithm can take observed trajectories from a wide variety of mechanicalsystems and, without any other prior knowledge or tuning of parameters, predictthe future evolution of the system. It does this by applying the principle ofleast action and searching for the simplest Lagrangian that describes thesystem's behaviour. By generating this Lagrangian in a human interpretableform, it also provides insight into the working of the system.

An algorithm for discovering Lagrangians automatically from data