20 citations · 22 across the 8 of their papers we have counts for
10 papers
Electronic excitation spectra and recovery of excited states with neural network wave functions
Xiaoyu Zhang, Weizhong Fu, Yixiao Chen
Accurate electronic spectra require both a flexible description of electron correlation and a tractable treatment of the many states contributing to the response. We combine neural…
Towards stable and accurate electron dynamics via neural network based time-dependent variational Monte Carlo
Weizhong Fu, Zhe Li, Yubing Qian +3
Real-time dynamics of interacting electrons lies at the interface between quantum mechanics and non-equilibrium physics, governing the microscopic origin of ultrafast phenomena of…
Permutation invariant multi-scale full quantum neural network wavefunction
Pengzhen Cai, Yubing Qian, Li Deng +8
Solving the intricate quantum behavior of interacting particles is key to unlocking the mysteries of condensed matter, but capturing their complex correlations across different sca…
Stochastic Representation of Time-Evolving Neural Network-based Wavefunctions
Bizi Huang, Weizhong Fu, Ji Chen
Solving the time-dependent Schrödinger equation (TDSE) is pivotal for modeling non-adiabatic electron dynamics, a key process in ultrafast spectroscopy and laser-matter interaction…
A particle view of many-body electronic structure with neural network wavefunction
Zichen Wang, Weizhong Fu, Zhe Li +2
In the study of electronic structure, the wavefunction view dominates the current research landscape and forms the theoretical foundation of modern quantum mechanics. In contrast,…
Neural Scaling Laws Surpass Chemical Accuracy for the Many-Electron Schrödinger Equation
Du Jiang, Xuelan Wen, Yixiao Chen +8
We demonstrate, for the first time, that neural scaling laws can deliver near-exact solutions to the many-electron Schrödinger equation across a broad range of realistic molecules.…
Empowering Neural Network-based Quantum Monte Carlo with Local Pseudopotentials
Weizhong Fu, Ryunosuke Fujimaru, Ruichen Li +9
Neural Network-based Quantum Monte Carlo (NNQMC), an emerging method for solving many-body quantum systems with high accuracy, has been mainly applied to small systems due to deman…
Penalty and auxiliary wave function methods for electronic Excitation in neural network variational Monte Carlo
Zixiang Lu, Weizhong Fu
This study explores the application of neural network variational Monte Carlo (NN-VMC) for the computation of low-lying excited states in molecular systems. Our focus lies on the i…
Variance extrapolation method for neural-network variational Monte Carlo
Weizhong Fu, Weiluo Ren, Ji Chen
Constructing more expressive ansatz has been a primary focus for quantum Monte Carlo, aimed at more accurate \textit{ab initio} calculations. However, with more powerful ansatz, e.…
Interatomic force from neural network based variational quantum Monte Carlo
Yubing Qian, Weizhong Fu, Weiluo Ren +1
Accurate ab initio calculations are of fundamental importance in physics, chemistry, biology, and materials science, which have witnessed rapid development in the last couple of ye…