The Frogs Method: A Bioinspired Algorithm For Micromagnetic Dynamics Skyrmion Data Extraction

TL;DR

This paper introduces a bio-inspired, frog-based Particle Swarm Optimization algorithm that accurately tracks skyrmion positions and internal structures in magnetic systems, overcoming limitations of traditional visualization methods.

Contribution

The paper presents a novel bio-inspired algorithm for skyrmion tracking that is reliable in discrete and finite boundary systems, providing detailed internal structure data.

Findings

Successfully tracks various skyrmion structures

Works reliably in discrete and bounded systems

Provides internal degrees of freedom information

Abstract

In this work we present a new bio-inspired method (using an adapted, frog based Particle Swarm Optimization) that can track a skyrmion's position. The structure and position of skyrmions in a given system is usually determined either by visual impression through a vector plot, or by averaging over magnetization and topological charge. Due to the inherent difficulty of acquiring this information in discrete systems, and also in systems with finite boundaries, we present a method which is able to reliably track a wide array of different topological structures, while also providing additional data about internal degrees of freedom, in both stationary and dynamic cases.