Design of k-space Magnon Dynamics by Machine Learning

Authors: Csaba, György, Ádám Papp, Horváth András, Joo-Von Kim, Maryam Massouras, Abdelmadjid Anane, Massimiliano d’Aquino, Salvatore Perna, and Claudio Serpico

We demonstrate the application of machnine learning techniques to the design of magnonic neuromorphic devices. Specifically, we show that these techniques are applicable not only to inverse-design propagating waves but to engineer the modal dynamics of nanomagnets in such a way that these magnets solve basic classification tasks.