Time-Delayed Dynamics in Regular Kuramoto Networks with Inertia: Multistability, Traveling Waves, Chimera States, and Transitions to Seizure-Like Activity

TL;DR

This paper explores how inertia and time delay influence the dynamics of regular Kuramoto networks, revealing multistability, traveling waves, chimera states, and seizure-like activity through analytical and numerical methods.

Contribution

It demonstrates the combined effects of inertia and time delay on stability and complex patterns in rotor networks, a novel insight into their interplay.

Findings

Time delays induce multistability among synchronized states.

Inertia destabilizes phase-locked states and reduces their attraction basin.

Inertia and delays promote chimera states and seizure-like dynamics.

Abstract

This study examines the complex interplay between inertia and time delay in regular rotor networks within the framework of the second-order Kuramoto model. By combining analytical and numerical methods, we demonstrate that intrinsic time delays -- arising from finite information transmission speeds - induce multistability among fully synchronized phase-locked states. Unlike systems without inertia, the presence of inertia destabilizes these phase-locked states, reduces their basin of attraction, and gives rise to nonlinear phase-locked dynamics over specific inertia ranges. In addition, we show that time delays promote the emergence of turbulent chimera states, while inertia enhances their spatial extent. Notably, the combined influence of inertia and time delay produces dynamic patterns reminiscent of partial epileptic seizures. These findings provide new insights into synchronization phenomena by revealing how inertia and time delay fundamentally reshape the stability and dynamics of regular rotor networks, with broader implications for neuronal modeling and other complex systems.