4 citations · 5 across the 3 of their papers we have counts for
4 papers
Symmetry enforced solution of the many-body Schrödinger equation with deep neural network
Zhe Li, Zixiang Lu, Ruichen Li +5
The integration of deep neural networks with the Variational Monte Carlo (VMC) method has marked a significant advancement in solving the Schrödinger equation. In this work, we enf…
Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo
Ruichen Li, Haotian Ye, Du Jiang +8
Neural network-based variational Monte Carlo (NN-VMC) has emerged as a promising cutting-edge technique of ab initio quantum chemistry. However, the high computational cost of exis…
Robust, accurate, and efficient: quantum embedding using the Huzinaga level-shift projection operator for complex systems
Daniel S. Graham, Xuelan Wen, Dhabih V. Chulhai +1
Wave function (WF) in density functional theory (DFT) embedding methods provide a framework for performing localized, high accuracy WF calculations on a system, while not incurring…
Absolutely Localized Projection-Based Embedding for Excited States
Xuelan Wen, Daniel S. Graham, Dhabih V. Chulhai +1
We present a quantum embedding method that allows for the calculation of local excited states embedded in a Kohn-Sham density functional theory (DFT) environment. Projection-based…