7 papers · 1 filter
Sum-of-Gaussians tensor neural networks for high-dimensional Schrödinger equation
Qi Zhou, Teng Wu, Jianghao Liu +3
We propose an accurate, efficient, and low-memory sum-of-Gaussians tensor neural network (SOG-TNN) algorithm for solving the high-dimensional Schrödinger equation. The SOG-TNN uti…
Random batch sum-of-Gaussians method for molecular dynamics simulation of particle systems in the NPT ensemble
Zhen Jiang, Jiuyang Liang, Qi Zhou
In this work, we develop a random batch sum-of-Gaussians (RBSOG) method for molecular dynamics simulations of charged systems in the isothermal-isobaric (NPT) ensemble. We introduc…
An Monte Carlo method for periodic Coulomb systems
Xuanzhao Gao, Shidong Jiang, Jiuyang Liang +1
Efficient Monte Carlo (MC) sampling of many-body systems with long-range electrostatics is often limited by the cost of per-move energy-difference evaluation under periodic boundar…
Symmetry-preserving random batch Ewald method for constant-potential simulation of electrochemical systems
Weihang Gao, Qi Zhou, Qianru Zhang +1
Constant potential molecular dynamics simulation plays important role for applications of electrochemical systems, yet the calculation of charge fluctuation on electrodes remains a…
Weighted balanced truncation method for approximating kernel functions by exponentials
Yuanshen Lin, Zhenli Xu, Yusu Zhang +1
Kernel approximation with exponentials is useful in many problems with convolution quadrature and particle interactions such as integral-differential equations, molecular dynamics…
Variance-reduced random batch Langevin dynamics
Zhenli Xu, Yue Zhao, Qi Zhou
The random batch method is advantageous in accelerating force calculations in particle simulations, but it poses a challenge of removing the artificial heating effect in applicatio…