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Main Authors: Arava, Hanu, Sanz-Hernandez, Dedalo, Grollier, Julie, Petford-Long, Amanda
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2407.06130
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author Arava, Hanu
Sanz-Hernandez, Dedalo
Grollier, Julie
Petford-Long, Amanda
author_facet Arava, Hanu
Sanz-Hernandez, Dedalo
Grollier, Julie
Petford-Long, Amanda
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2407_06130
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Real Space Imaging of Field-Driven Decision-Making in Nanomagnetic Galton Boards
Arava, Hanu
Sanz-Hernandez, Dedalo
Grollier, Julie
Petford-Long, Amanda
Applied Physics
Materials Science
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.
title Real Space Imaging of Field-Driven Decision-Making in Nanomagnetic Galton Boards
topic Applied Physics
Materials Science
url https://arxiv.org/abs/2407.06130