Adaptation to synchronization in phase-oscillator networks

TL;DR

This paper presents an adaptation algorithm for coupled oscillators that achieves prescribed synchronization by modifying microscopic interactions based on macroscopic synchronization measures, inspired by biological evolution and learning.

Contribution

It introduces a novel adaptation scheme that adjusts repulsive interactions in oscillator networks to reach desired synchronization states.

Findings

Successfully induces prescribed synchronization in oscillator networks.

Demonstrates adaptation effectiveness through microscopic interaction modifications.

Emulates biological evolution and learning mechanisms.

Abstract

We introduce an adaptation algorithm by which an ensemble of coupled oscillators with attractive and repulsive interactions is induced to adopt a prescribed synchronized state. While the performance of adaptation is controlled by measuring a macroscopic quantity, which characterizes the achieved degree of synchronization, adaptive changes are introduced at the microscopic level of the interaction network, by modifying the configuration of repulsive interactions. This scheme emulates the distinct levels of selection and mutation in biological evolution and learning.