Web: http://arxiv.org/abs/2206.07370

June 16, 2022, 1:10 a.m. | Cong Fu, Xuan Zhang, Huixin Zhang, Hongyi Ling, Shenglong Xu, Shuiwang Ji

cs.LG updates on arXiv.org arxiv.org

Deep learning methods have been shown to be effective in representing
ground-state wave functions of quantum many-body systems. Existing methods use
convolutional neural networks (CNNs) for square lattices due to their
image-like structures. For non-square lattices, existing method uses graph
neural network (GNN) in which structure information is not precisely captured,
thereby requiring additional hand-crafted sublattice encoding. In this work, we
propose lattice convolutions in which a set of proposed operations are used to
convert non-square lattices into grid-like augmented …

arxiv learning networks quantum systems

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