45 citations · 51 across the 3 of their papers we have counts for
4 papers
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…
Manipulation of Spin Dynamics by Deep Reinforcement Learning Agent
Jun-Jie Chen, Ming Xue
We implement the reinforcement learning agent for a spin-1 atomic system to prepare spin squeezed state from given initial state. Proximal policy gradient (PPO) algorithm is used t…
Universal driven critical dynamics across a quantum phase transition in ferromagnetic spinor atomic Bose-Einstein condensates
Ming Xue, Shuai Yin, Li You
We study the equilibrium and dynamical properties of a ferromagnetic spinor atomic Bose-Einstein condensate. In the vicinity of the critical point for a continuous quantum phase tr…