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

The use of stochastic models, in effect piecewise deterministic Markovprocesses (PDMP), has become increasingly popular especially for the modelingof chemical reactions and cell biophysics. Yet, exact simulation methods, forthe simulation of these models in evolving environments, are limited by theneed to find the next jumping time at each recursion of the algorithm. Here, wereport on a new general method to find this jumping time for the True JumpMethod. It is based on an expression in terms of ordinary differentialequations for which efficient numerical methods are available. As such, our newresult makes it possible to study numerically stochastic models for whichanalytical formulas are not available thereby providing a way to approximatethe state distribution for example. We conclude that the wide use of eventdetection schemes for the simulation of PDMPs should be strongly reconsidered.The only relevant remaining question being the efficiency of our methodcompared to the Fictitious Jump Method, question which is strongly casedependent.

A new twist for the simulation of hybrid systems using the true jump method