Name
Abstract | ||
|---|---|---|
Given two distinct subsetsA, Bin the state space of some dynamical system, transition path theory (TPT) was successfully used to describe the statistical behavior of transitions fromAtoBin the ergodic limit of the stationary system. We derive generalizations of TPT that remove the requirements of stationarity and of the ergodic limit and provide this powerful tool for the analysis of other dynamical scenarios: periodically forced dynamics and time-dependent finite-time systems. This is partially motivated by studying applications such as climate, ocean, and social dynamics. On simple model examples, we show how the new tools are able to deliver quantitative understanding about the statistical behavior of such systems. We also point out explicit cases where the more general dynamical regimes show different behaviors to their stationary counterparts, linking these tools directly to bifurcations in non-deterministic systems. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s00332-020-09652-7 | JOURNAL OF NONLINEAR SCIENCE |
Keywords | DocType | Volume |
Transition path theory,Markov chains,Time-inhomogeneous process,Periodic driving,Finite-time dynamics | Journal | 30 |
Issue | ISSN | Citations |
6 | 0938-8974 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luzie Helfmann | 1 | 0 | 0.34 |
| Enric Ribera Borrell | 2 | 0 | 0.34 |
| Christof Schütte | 3 | 167 | 35.19 |
| Péter Koltai | 4 | 19 | 3.87 |