Deep learning-enhanced variational Monte Carlo method for quantum many-body physics

Li Yang, Zhaoqi Leng, Guangyuan Yu, Ankit Patel, Wen-Jun Hu, Han Pu

Type: Article

Publication Date: 2020-02-14

Citations: 36

DOI: https://doi.org/10.1103/physrevresearch.2.012039

Abstract

The authors construct and develop an optimization scheme to train a deep convolutional neural network to represent many-body wave function. The paper explores its performance by applying the network to find the ground state of an SU(N) spin-chain Hamiltonian using variational quantum Monte Carlo.

Locations

Physical Review Research - View - PDF
arXiv (Cornell University) - View - PDF
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) - View
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