graph neural networks 1machine learning potentials 1magnetic force fields 1metallic magnets 1spin dynamics 1
From the 1 of 3 linked papers with an AI index.
3 papers
cond-mat.str-el2026
Graph Neural Network Force Fields for Spin Dynamics in Metallic Magnets
Ali Rayat, Yunhao Fan, Gia-Wei Chern
The paper presents a graph neural network framework that learns magnetic force fields from electronic calculations to efficiently simulate spin dynamics in metallic magnets, reprod…
cond-mat.str-el2026
Graph Neural Networks in the Wilson Loop Representation of Abelian Lattice Gauge Theories
Ali Rayat, Gia-Wei Chern
Local gauge structures play a central role in a wide range of condensed matter systems and synthetic quantum platforms, where they emerge as effective descriptions of strongly corr…
cond-mat.str-el2026
Gauge-Equivariant Graph Neural Networks for Lattice Gauge Theories
Ali Rayat, Yaohang Li, Gia-Wei Chern
Local gauge symmetry underlies fundamental interactions and strongly correlated quantum matter, yet existing machine-learning approaches lack a general, principled framework for le…