Machine learning inspired models for Hall effects in non-collinear magnets

Machine learning inspired models for Hall effects in non-collinear magnets

The anomalous Hall effect has been front and center in solid state research and material science for over a century now, and the complex transport phenomena in nontrivial magnetic textures have gained an increasing amount of attention, both in theoretical and experimental studies. However, a clear p...

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Bibliographic Details
Main Authors: Jonathan Kipp, Fabian R Lux, Thorben Pürling, Abigail Morrison, Stefan Blügel, Daniele Pinna, Yuriy Mokrousov
Format: Article
Language:English
Published: IOP Publishing 2024-01-01
Series:Machine Learning: Science and Technology
Subjects:
anomalous Hall effect
machine learning
crystal symmetry
principal component analysis
magnetism
Online Access:https://doi.org/10.1088/2632-2153/ad51ca

Internet

https://doi.org/10.1088/2632-2153/ad51ca

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