Bifurcation Analysis using Zigzag PersistenceDownload PDF

Oct 10, 2020 (edited Dec 02, 2020)NeurIPS 2020 Workshop TDA and Beyond Blind SubmissionReaders: Everyone
  • Keywords: topological data analysis, time series analysis, zigzag persistence
  • TL;DR: We develop a novel method of using zigzag persistence to detect Hopf bifurcations in dynamical systems.
  • Abstract: As bifurcations in a dynamical system are drastic behavioral changes, being able to detect when these bifurcations occur can be essential to understanding the system overall. While persistent homology has successfully been used in the field of dynamical systems, the most commonly used approaches have their limitations. Using zigzag persistence, we can simplify the methodology and capture topological changes through a collection of time series, rather that studying the topology of individual time series separately. Here we present Bifurcations using ZigZag (BuZZ), a method to detect Hopf bifurcations in dynamical systems.
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