JinGuo Liu
Zitiert von
Zitiert von
Approximating quantum many-body wave functions using artificial neural networks
Z Cai, J Liu
Physical Review B 97 (3), 035116, 2018
Differentiable learning of quantum circuit born machines
JG Liu, L Wang
Physical Review A 98 (6), 062324, 2018
Superconductivity in doped : A functional renormalization group study
Y Yang, WS Wang, JG Liu, H Chen, JH Dai, QH Wang
Physical Review B 89 (9), 094518, 2014
Differentiable programming tensor networks
HJ Liao, JG Liu, L Wang, T Xiang
Physical Review X 9 (3), 031041, 2019
Variational quantum eigensolver with fewer qubits
JG Liu, YH Zhang, Y Wan, L Wang
Physical Review Research 1 (2), 023025, 2019
Learning and inference on generative adversarial quantum circuits
J Zeng, Y Wu, JG Liu, L Wang, J Hu
Physical Review A 99 (5), 052306, 2019
Yao. jl: Extensible, efficient framework for quantum algorithm design
XZ Luo, JG Liu, P Zhang, L Wang
Quantum 4, 341, 2020
Quantum impurities in channel mixing baths
JG Liu, D Wang, QH Wang
Physical Review B 93 (3), 035102, 2016
Solving quantum statistical mechanics with variational autoregressive networks and quantum circuits
JG Liu, L Mao, P Zhang, L Wang
Machine Learning: Science and Technology 2 (2), 025011, 2021
Electronic order near the type-II van Hove singularity in
Y Wang, JG Liu, WS Wang, QH Wang
Physical Review B 97 (17), 174513, 2018
Automatic differentiation of dominant eigensolver and its applications in quantum physics
H Xie, JG Liu, L Wang
Physical Review B 101 (24), 245139, 2020
Local indistinguishability and edge modes revealed by the sub-system fidelity
JG Liu, ZL Gu, JX Li, QH Wang
New Journal of Physics 19 (9), 093017, 2017
Tropical tensor network for ground states of spin glasses
JG Liu, L Wang, P Zhang
arXiv preprint arXiv:2008.06888, 2020
Differentiate Everything with a Reversible Programming Language
JG Liu, T Zhao
arXiv preprint arXiv:2003.04617, 2020
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