Approximate solution to the stochastic Kuramoto model

TL;DR

This paper develops a Gaussian approximation method to analytically solve the stochastic Kuramoto model, accurately predicting synchronization behavior and critical coupling, including in complex networks.

Contribution

It introduces a Gaussian approximation that reduces the stochastic Kuramoto model to two differential equations, providing an exact critical coupling and closed-form asymptotic order parameter.

Findings

Analytical solution matches numerical results below and above critical coupling

Exact critical coupling strength recovered by the Gaussian theory

Closed-form asymptotic order parameter derived

Abstract

We study Kuramoto phase oscillators with temporal fluctuations in the frequencies. The infinite-dimensional system can be reduced in a Gaussian approximation to two first-order differential equations. This yields a solution for the \emph{time-dependent} order parameter, which characterizes the synchronization between the oscillators. The known critical coupling strength is exactly recovered by the Gaussian theory. Extensive numerical experiments further show that the analytical results are very accurate below and sufficiently above the critical value. We obtain the asymptotic order parameter \emph{in closed form}, which suggests a tighter upper bound for the corresponding scaling. As a last point, we elaborate the Gaussian approximation in complex networks with distributed degrees.