Ferromagnetic skyrmionium-based artificial neuron devices using magnetic field gradients

Skyrmioniums are protected topological textures that have potential applications in spintronics. This study demonstrates the feasibility of simulating an artificial neuron device with leaky-integrate-and-fire (LIF) functionality on a ferromagnetic racetrack using micromagnetic simulations. First, we determine the magnetic field range required to stabilize a skyrmionium. Then, we show that applying a magnetic field gradient enables the controlled displacement of a skyrmionium along the racetrack. Our results indicates that the displacement speed increases with a stronger gradient intensity or a lower damping constant. These findings agree with those predicted by the Thiele equation. We also demonstrate that applying current pulses along with a magnetic field gradient makes it possible to emulate LIF functionality on a racetrack, using skyrmioniums as a fundamental building block.