Mapping the magnonic landscape in patterned magnetic structures - article

This is the author accepted manuscript. The final version is available from American Physical Society via the DOI in this record.The software associated with this article is in ORE at http://hdl.handle.net/10871/29479There is another ORE record for both the article and the software: http://hdl.handle.net/10871/31173We report the development of a hybrid numerical / analytical model capable of mapping the spatially-varying distributions of the local ferromagnetic resonance (FMR) frequency and dynamic magnetic susceptibility in a wide class of patterned and compositionally modulated magnetic structures. Starting from the numerically simulated static micromagnetic state, the magnetization is deliberately deflected orthogonally to its equilibrium orientation, and the magnetic fields generated in response to this deflection are evaluated using micromagnetic software. This allows us to calculate the elements of the effective demagnetizing tensor which are then used within a linear analytical formalism to map the local FMR frequency and dynamic magnetic susceptibility. To illustrate the typical results that one can obtain using this model, we analyze three micromagnetic systems boasting non-uniformity in either one or two dimensions, and successfully explain the spin-wave emission observed in each case, demonstrating the ubiquitous nature of the Schlömann excitation mechanism underpinning the observations. Finally, the developed model of local FMR frequency could be used to explain how spin waves could be confined and steered using magnetic non-uniformities of various origins, rendering it a powerful tool for the mapping of the graded magnonic index in magnonics.The research leading to these results has received funding from the Engineering and Physical Sciences Research Council of the United Kingdom (Project Nos. EP/L019876/1 and EP/P505526/1), and from the European Union’s Horizon 2020 research and innovation program under Marie Skłodowska-Curie Grant Agreement No. 644348 (MagIC)