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@PHDTHESIS{Kipp:996251,
author = {Kipp, Jonathan Martin},
othercontributors = {Honerkamp, Carsten and Mokrousov, Yuriy},
title = {{M}achine learning models for chiral transport in magnetic
systems},
school = {RWTH Aachen University},
type = {Dissertation},
address = {Aachen},
publisher = {RWTH Aachen University},
reportid = {RWTH-2024-10466},
pages = {1 Online-Ressource : Illustrationen},
year = {2024},
note = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
University; Dissertation, RWTH Aachen University, 2024},
abstract = {Achievements in the field of solid state physics have
shaped our way of life profoundly over the last century,
propelling mankind into an era of wearable electronics,
worldwide access to electronically stored information, and
computing power previously unheard of. Mobile phones, which
can be found in almost everyone's pocket today, perfectly
illustrate the pivotal conflict between simultaneous
miniaturization of devices and increases in computing power
and storage density, that has been at the heart of solid
state research since the fabrication of the world's first
transistor. In addition, there is much interest in computing
architectures beyond the standard, semiconductor-based
computers. Now, materials with non-collinear magnetization
textures, such as domain walls or skyrmions, present
themselves as prime candidates in the quest for miniature
electronics and unconventional computing platforms alike,
due to their small size, their stability, and their
intrinsic, non-linear characteristics, enabling complex
arithmetic operations. However, a clear description of
charge, heat, or spin transport in complex magnetization
textures is still sought after. Therefore, a systematic way
of conquering the complexity in canted magnets or chiral
textures is a key objective in the field of spintronics. In
this thesis, explicit tight-binding calculations of the
anomalous Hall effect on a two-dimensional, magnetic
honeycomb lattice, are exploited in a threefold manner in
order to introduce the vector chirality of a magnetic
texture as a powerful order parameter. First, the chiral
Hall effect in canted magnets is established on equal
footing with the anomalous Hall effect of collinear
ferromagnets and antiferromagnets, by identifying the chiral
Hall effect as the contribution to the anomalous Hall effect
linear in vector chirality. Second, by classifying different
parts of the Hall signal with respect to the vector
chirality of the magnetic configuration and the underlying
crystal symmetry, the numerical data reproduces the
functional form and directional dependence obtained from an
expansion of the anomalous Hall effect in gradients of the
magnetization. Lastly, numerical data is utilized for
training a linear model of the anomalous Hall effect,
encompassing effects up to arbitrary order in the
magnetization, which is constructed from the symmetric
invariants of the lattice symmetry. Through explicitly
training non-chiral and chiral models, this constructive
method demonstrates the fingerprint of chiral magnetic
textures in electric transport properties.},
cin = {135510 / 130000},
ddc = {530},
cid = {$I:(DE-82)135510_20140620$ / $I:(DE-82)130000_20140620$},
typ = {PUB:(DE-HGF)11},
doi = {10.18154/RWTH-2024-10466},
url = {https://publications.rwth-aachen.de/record/996251},
}
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