This project addresses fundamental aspects of out-of-equilibrium driven magnetic skyrmion dynamics. We utilize the effect of topology on magnetization dynamics to design platforms for the controlled emission of nanoscale spin-waves with tunable characteristics linked to the topology of the source, applicable to a large variety of skyrmion-hosting materials. We study the dynamics of magnetic skyrmions on deformable geometries and reveal that novel curvature-driven effects emerge in geometries with non-constant curvature. While the conventional data storage technology is gradually reaching its limits, skyrmion-based devices hold great promise as a basis for a new type of information technology. To utilize skyrmions in future storage devices, it is necessary to understand and control their response to external fields.
We also design new physical qubits for quantum computing based on topological skyrmions. We construct several qubit archetypes by engineering the potential energy landscape using impurity defects, external fields, geometrical confinement and tailored heterostructures. The logical states can be adjusted by electric and magnetic fields, offering a rich operation regime with high anharmonicity. We propose microwave magnetic field gradients for skyrmion qubit manipulation and gate operation, and consider skyrmion multiqubit schemes for a scalable architecture. Quantum computing holds the promise of improving computer performance, with many applications including material design and drug development. We introduce a new class of qubits based on skyrmions examine a few traditional requirements including the ability to initialize, coherently control and measure the quantum state, as well as long coherence times. Scalability, controllability by microwave fields, operation time scales, and readout by nonvolatile techniques converge to make the skyrmion qubit highly attractive as a logical element of a quantum processor.
Moreover, we consider periodically driven magnetic systems coupled to a quantum cavity as a new platform for the efficient transfer of photons from one electromagnetic mode to another. We explore the frequency conversion problem through optimazation techniques of the corresponding Floquet Hamiltonian using Machine Learning and Deep Learning techniques. The development of efficient frequency conversion mechanisms is a process with various technological applications, relevant for quantum communications and quantum computing and a cornerstone of quantum machines and amplifiers.
We explore new ways to probe and utilize magnetic skyrmion dynamics and examine the extent to which they can enable superior future technologies. Our work addresses fundamental aspects of the skyrmion physics that are especially relevant for applications. We also explore novel functionalities for magnetic skyrmions by considering their dynamics in tailored curved geometries. Our work on skyrmion qubits lies at the intersection of two otherwise disconnected research directions, the field of qubits, aiming to develop a quantum computer, and the field of skyrmionics, intending to design future spintronic devices based on magnetic skyrmions. It introduces an entirely new direction to the former and an unexplored avenue for the latter.
