Reconfigurable spin-wave platform based on interplay between nanodots and waveguide in hybrid magnonic crystal

TL;DR

This paper introduces a reconfigurable hybrid magnonic crystal combining nanodots and a waveguide, demonstrating complex spin-wave behaviors and potential for advanced magnonic applications.

Contribution

It presents a novel hybrid magnonic crystal with tunable properties based on nanodot states and their interaction with a waveguide, expanding the functionalities of magnonic devices.

Findings

Complex spin-wave spectra with multiple band gaps.

Presence of flat bands and hybridized modes in skyrmion states.

Broad frequency range of waveguide-dominated modes in single-domain state.

Abstract

We present a hybrid magnonic crystal composed of a chain of nanodots with strong perpendicular magnetic anisotropy and Dzyaloshinskii-Moriya interaction, positioned above a permalloy waveguide. The micromagnetic study examines two different magnetization states in the nanodots: a single-domain state and an egg-shaped skyrmion state. Due to the dipolar coupling between the dot and the waveguide, a strongly bound hybrid magnetization texture is formed in the system. Our results show complex spin-wave spectra, combining the effects of periodicity, magnetization texture, and hybridization of the propagating waves in the waveguide with the dot/skyrmion modes. The dynamics of the systems are characterized by several key features which include differences in band-gap sizes, the presence of flat bands in the skyrmion state that can form both bound and hybridized states, the latter sometimes leading to the presence of additional non-Bragg band gaps, and a broad frequency range of only waveguide-dominated modes in the single-domain state. Thus, the study shows that the proposed hybrid magnonic crystals have many distinct functionalities, highlighting their reconfigurable potential, magnon-magnon couplings, mode localization, and bound states overlapping with the propagating waves. This opens up potential applications in analog and quantum magnonics, spin-wave filtering, and the establishment of magnonic neural networks.