Design of k-space Magnon Dynamics by Machine Learning
- Resource Type
- Conference
- Authors
- Csaba, Gyorgy; Papp, Adam; Andras, Horvath; Kim, Joo-Von; Massouras, Maryam; Anane, Abdelmadjid; d'Aquino, Massimiliano; Perna, Salvatore; Serpico, Claudio
- Source
- 2023 IEEE International Magnetic Conference - Short Papers (INTERMAG Short Papers) Magnetic Conference - Short Papers (INTERMAG Short Papers), 2023 IEEE International. :1-2 May, 2023
- Subject
- Fields, Waves and Electromagnetics
Magnonics
Neuromorphics
Computational modeling
Machine learning
Task analysis
backpropagation
k-space computing
normal modes model
vowel classifiaction
- Language
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.