HubbardNet: Efficient predictions of the Bose-Hubbard model spectrum with deep neural networks
We present a deep neural network (DNN) -based model (HubbardNet) to variationally find the ground-state and excited-state wave functions of the one-dimensional and two-dimensional Bose-Hubbard model. Using this model for a square lattice with M sites, we obtain the energy spectrum as an analytical f...
Main Authors: | Ziyan Zhu, Marios Mattheakis, Weiwei Pan, Efthimios Kaxiras |
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Format: | Article |
Language: | English |
Published: |
American Physical Society
2023-10-01
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Series: | Physical Review Research |
Online Access: | http://doi.org/10.1103/PhysRevResearch.5.043084 |
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