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Evaluating the phase dynamics of coupled oscillators via time-variant topological features
- Publication Year :
- 2020
-
Abstract
- By characterizing the phase dynamics in coupled oscillators, we gain insights into the fundamental phenomena of complex systems. The collective dynamics in oscillatory systems are often described by order parameters, which are insufficient for identifying more specific behaviors. To improve this situation, we propose a topological approach that constructs the quantitative features describing the phase evolution of oscillators. Here, the phase data are mapped into a high-dimensional space at each time, and the topological features describing the shape of the data are subsequently extracted from the mapped points. These features are extended to time-variant topological features by adding the evolution time as an extra dimension in the topological feature space. The time-variant features provide crucial insights into the evolution of phase dynamics. Combining these features with the kernel method, we characterize the multi-clustered synchronized dynamics during the early evolution stages. Finally, we demonstrate that our method can qualitatively explain chimera states. The experimental results confirmed the superiority of our method over those based on order parameters, especially when the available data are limited to the early-stage dynamics.<br />13 pages, 8 figures
- Subjects :
- FOS: Computer and information sciences
Computer Science - Machine Learning
Computer science
Feature vector
Phase (waves)
Complex system
FOS: Physical sciences
Probability and statistics
Topology
Space (mathematics)
Nonlinear Sciences - Chaotic Dynamics
01 natural sciences
010305 fluids & plasmas
Machine Learning (cs.LG)
Kernel method
Order (biology)
Dimension (vector space)
Physics - Data Analysis, Statistics and Probability
0103 physical sciences
FOS: Mathematics
Algebraic Topology (math.AT)
Mathematics - Algebraic Topology
Chaotic Dynamics (nlin.CD)
010306 general physics
Data Analysis, Statistics and Probability (physics.data-an)
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....e333d09d5ea54500300538c31afd5275