45 citations · 73 across the 3 of their papers we have counts for
3 papers
cond-mat.dis-nn2022
Neural network quantum state with proximal optimization: a ground-state searching scheme based on variational Monte Carlo
Feng Chen, Ming Xue
Neural network quantum states (NQS), incorporating with variational Monte Carlo (VMC) method, are shown to be a promising way to investigate quantum many-body physics. Whereas vani…
cond-mat.quant-gas2020★ 45 cited
Faster State Preparation across Quantum Phase Transition Assisted by Reinforcement Learning
Shuai-Feng Guo, Feng Chen, Qi Liu +6
An energy gap develops near quantum critical point of quantum phase transition in a finite many-body (MB) system, facilitating the ground state transformation by adiabatic paramete…
cond-mat.quant-gas2019★ 28 cited
Extreme Spin Squeezing from Deep Reinforcement Learning
Feng Chen, Jun-Jie Chen, Ling-Na Wu +2
Spin squeezing (SS) is a recognized resource for realizing measurement precision beyond the standard quantum limit . The rudimentary one-axis twisting (OAT) int…