45 citations · 87 across the 4 of their papers we have counts for
5 papers
Detection of entangled states supported by reinforcement learning
Jia-Hao Cao, Feng Chen, Qi Liu +4
Discrimination of entangled states is an important element of quantum enhanced metrology. This typically requires low-noise detection technology. Such a challenge can be circumvent…
Quantum enhanced sensing by echoing spin-nematic squeezing in atomic Bose-Einstein condensate
Tian-Wei Mao, Qi Liu, Xin-Wei Li +6
Quantum entanglement can provide enhanced precision beyond standard quantum limit (SQL), the highest precision achievable with classical means. It remains challenging, however, to…
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…
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…
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…