Low dimensional behaviour of generalized Kuramoto model
Sara Ameli, and Keivan Aghababaei Samani

TL;DR
This paper analyzes the low-dimensional dynamics and bifurcations of a generalized Kuramoto model with frequency-weighted coupling, revealing different synchronization transition types through analytical and numerical methods.
Contribution
It provides a reduced four- and two-dimensional analytical framework for understanding bifurcations in the frequency-weighted Kuramoto model with symmetric Lorentzian distributions.
Findings
Identified three types of synchronization transitions: two-step, continuous, and first-order with hysteresis.
Derived the stability diagram and bifurcation boundaries analytically.
Confirmed analytical results with numerical simulations.
Abstract
We study the global bifurcations of frequency weighted Kuramoto model in low-dimension for network of fully connected oscillators. To study the effect of non-zero-centered frequency distribution, we consider two symmetric Lorentzians as an example. We derive the stability diagram of the system and show that the infinite-dimensional problem reduces to a flow in four dimensions. Using the system symmetries, it can be further reduced to two dimensions. Using this analytic framework, we obtain bifurcation boundaries of the system, which is compatible with our numeric simulations. We show that the system has three types of transitions to synchronized state for different parameters of the frequency distribution: (1) a two-step transition, representative of standing waves, (2) a continuous transition, as in the classical Kuramoto model, and (3) a first-order transition with hysteresis.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNonlinear Dynamics and Pattern Formation · Slime Mold and Myxomycetes Research · Ecosystem dynamics and resilience
