English

Scaling Limit of the Kuramoto Model on Random Geometric Graphs

Probability 2025-06-03 v3 Analysis of PDEs

Abstract

We consider the Kuramoto model on a graph with nodes given by nn i.i.d. points uniformly distributed on the dd dimensional torus. Two nodes are declared neighbors if they are at distance less than ϵ\epsilon. We prove a scaling limit for this model in compact time intervals as nn\to\infty and ϵ0\epsilon \to 0 such that ϵd+2n/logn\epsilon^{d+2}n/\log n \to \infty. The limiting object is given by the heat equation. On the one hand this shows that the nonlinearity given by the sine function disappears under this scaling and on the other hand, provides evidence that stable equilibria of the Kuramoto model on these graphs are, as nn\to\infty, in correspondence with those of the heat equation, which are explicit and given by twisted states. In view of this, we conjecture the existence of twisted stable equilibria with high probability as nn\to \infty.

Keywords

Cite

@article{arxiv.2402.15311,
  title  = {Scaling Limit of the Kuramoto Model on Random Geometric Graphs},
  author = {Francisco Cirelli and Pablo Groisman and Ruojun Huang and Hernán Vivas},
  journal= {arXiv preprint arXiv:2402.15311},
  year   = {2025}
}