184 citations · 727 across the 14 of their papers we have counts for
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cond-mat.str-el2020★ 56 cited
Correlator Convolutional Neural Networks: An Interpretable Architecture for Image-like Quantum Matter Data
Cole Miles, Annabelle Bohrdt, Ruihan Wu +7
Machine learning models are a powerful theoretical tool for analyzing data from quantum simulators, in which results of experiments are sets of snapshots of many-body states. Recen…
cond-mat.quant-gas2020★ 73 cited
Coupling a mobile hole to an antiferromagnetic spin background: Transient dynamics of a magnetic polaron
Geoffrey Ji, Muqing Xu, Lev Haldar Kendrick +8
Understanding the interplay between charge and spin and its effects on transport is a ubiquitous challenge in quantum many-body systems. In the Fermi-Hubbard model, this interplay…