English

Synchronization of mean-field models on the circle

Dynamical Systems 2025-07-31 v1 Machine Learning Analysis of PDEs Optimization and Control

Abstract

This paper considers a mean-field model of nn interacting particles whose state space is the unit circle, a generalization of the classical Kuramoto model. Global synchronization is said to occur if after starting from almost any initial state, all particles coalesce to a common point on the circle. We propose a general synchronization criterion in terms of L1L_1-norm of the third derivative of the particle interaction function. As an application we resolve a conjecture for the so-called self-attention dynamics (stylized model of transformers), by showing synchronization for all β0.16\beta \ge -0.16, which significantly extends the previous bound of 0β10\le \beta \le 1 from Criscitiello, Rebjock, McRae, and Boumal (2024). We also show that global synchronization does not occur when β<2/3\beta < -2/3.

Keywords

Cite

@article{arxiv.2507.22857,
  title  = {Synchronization of mean-field models on the circle},
  author = {Yury Polyanskiy and Philippe Rigollet and Andrew Yao},
  journal= {arXiv preprint arXiv:2507.22857},
  year   = {2025}
}