3 papers
cond-mat.str-el2025
Deep Learning Sheds Light on Integer and Fractional Topological Insulators
Xiang Li, Yixiao Chen, Bohao Li +4
Electronic topological phases of matter, characterized by robust boundary states derived from topologically nontrivial bulk states, are pivotal for next-generation electronic devic…
cond-mat.str-el2024
Taming Landau level mixing in fractional quantum Hall states with deep learning
Yubing Qian, Tongzhou Zhao, Jianxiao Zhang +3
Strong correlation brings a rich array of emergent phenomena, as well as a daunting challenge to theoretical physics study. In condensed matter physics, the fractional quantum Hall…
cond-mat.str-el2024
Probing quantum critical phase from neural network wavefunction
Haoxiang Chen, Weiluo Ren, Xiang Li +1
One-dimensional (1D) systems and models provide a versatile platform for emergent phenomena induced by strong electron correlation. In this work, we extend the newly developed real…