Article published in Nature Communications November 23, 2021

Nanoscale neural network using non-linear spin-wave interference

Two of our Faculty members, György Csaba PhD, associate professor and Ádám Papp PhD, research fellow, have recently published an article in Nature Communications, together with Professor Wolfgang Porod (Center for Nano Science and Technology University of Notre Dame (NDnano), Notre Dame, IN, USA).

Nature Communications is an open access, multidisciplinary journal dedicated to publishing high-quality research in all areas of the biological, health, physical, chemical and Earth sciences. Papers published by the journal aim to represent important advances of significance to specialists within each field.

Below you can read the Abstract of their article.

We demonstrate the design of a neural network hardware, where all neuromorphic computing functions, including signal routing and nonlinear activation are performed by spin-wave propagation and interference. Weights and interconnections of the network are realized by a magnetic-field pattern that is applied on the spin-wave propagating substrate and scatters the spin waves. The interference of the scattered waves creates a mapping between the wave sources and detectors. Training the neural network is equivalent to finding the field pattern that realizes the desired input-output mapping. A custom-built micromagnetic solver, based on the Pytorch machine learning framework, is used to inverse-design the scatterer. We show that the behavior of spin waves transitions from linear to nonlinear interference at high intensities and that its computational power greatly increases in the nonlinear regime. We envision small-scale, compact and low-power neural networks that perform their entire function in the spin-wave domain.

The full article can be reached here.