Speaker
Description
Magnetic vortices, with their topologically protected spin textures, excellent stability, and rich dynamical behavior, have emerged as promising building blocks for next-generation spintronic devices. Their controllable polarity, chirality, and gyrotropic motion offer exciting opportunities for developing energy-efficient memories, microwave oscillators, and unconventional computing architectures. Here we discuss recent advances in the computational design and micromagnetic simulation of vortex-based nanostructures for information storage and processing.
We demonstrate how geometric and interfacial engineering in bi-component bow-tie nanostructures enables the formation of multiple stable vortex and vortex–antivortex configurations. These multistable states provide an effective route toward high-density multi-bit magnetic memory. It then explores frequency tuning in spin-torque vortex oscillators through localized modification of magnetic material properties, leading to improved resonance control, enhanced spectral purity, and optimized microwave performance. The collective dynamics of dipolar-coupled vortex lattices are also discussed, highlighting coherent gyrotropic modes and efficient magnetic energy transfer for future magnonic and wave-based computing technologies.
We also discuss the emerging role of a data-driven approach to accelerate the prediction and control of vortex dynamics. Particular emphasis is placed on magnetic field sequence-driven vortex state dynamics, in which carefully designed sequences of magnetic field pulses produce deterministic switching among multiple vortex states. Learning the relationship between field sequences and vortex responses enables rapid optimization of switching pathways, paving the way for programmable information storage, reservoir computing, sequence recognition, and intelligent spintronic information processing.
These advances together establish magnetic vortices as a versatile platform for future scalable, low-power memory, computing, and neuromorphic systems.