2024/07/08 by Hanu Arava, Arava, Hanu, Dédalo Sanz‐Hernández +5 · 1 citation
Engineering · #Applied Physics (physics.app-ph) #Characterization and Applications of Magnetic Nanoparticles #FOS: Physical sciences #Magnetic Field Sensors Techniques #Materials Science (cond-mat.mtrl-sci)
paper · pdf · doi:10.48550/arxiv.2407.06130
openalex publication_date 2024/07/08 · openalex created_date 2024/07/11 · openalex updated_date 2026/07/31
A possible spintronic route to hardware implementation for decision making involves injecting a domain wall into a bifurcated magnetic nanostrip resembling a Y-shaped junction. A decision is made when the domain wall chooses a particular path through the bifurcation. Recently, it was shown that a structure like a nanomagnetic Galton Board, which is essentially an array of interconnected Y-shaped junctions, produces outcomes that are stochastic and therefore relevant to artificial neural networks. However, the exact mechanism leading to the robust nature of randomness is unknown. Here, we directly image the decision-making process in nanomagnetic Galton Boards using Lorentz transmission electron microscopy. We identify that the stochasticity in nanomagnetic Galton Boards arises as a culmination of: (1) topology of the injected domain wall, (2) local disorder, and (3) strength of the applied field. Our results pave the way to a detailed understanding of stochasticity in nanomagnetic networks.