Title
Detecting and Locating Near-Optimal Almost-Invariant Sets and Cycles
Abstract
The behaviors of trajectories of nonlinear dynamical systems are notoriously hard to characterize and predict. Rather than characterizing dynamical behavior at the level of trajectories, we consider following the evolution of sets. There are often collections of sets that behave in a very predictable way, in spite of the fact that individual trajectories are entirely unpredictable. Such special collections of sets are invisible to studies of long trajectories. We describe a global set-oriented method to detect and locate these large dynamical structures. Our approach is a marriage of new ideas in modern dynamical systems theory and the novel application of graph dissection algorithms.
Year
DOI
Venue
2003
10.1137/S106482750238911X
SIAM J. Scientific Computing
Keywords
Field
DocType
almost-invariant set,almost-cycle,macrostructure,Fiedler vector,graph partitioning,minimal cut,maximal cut,Laplacian matrix
Cut,Laplacian matrix,Mathematical optimization,Combinatorics,Stochastic matrix,Algorithm,Algebraic connectivity,Dynamical systems theory,Invariant (mathematics),Graph partition,Mathematics,Dynamical system
Journal
Volume
Issue
ISSN
24
6
1064-8275
Citations 
PageRank 
References 
16
3.48
2
Authors
2
Name
Order
Citations
PageRank
Gary Froyland113017.19
Michael Dellnitz217420.34