12 papers
Prolate spheroidal wave functions enable fast and exponent-aware long-range machine learning interatomic potentials
Jiuyang Liang, Libin Lu, Yajie Ji +1
Long-range interactions such as electrostatics and dispersion remain a central bottleneck for machine learning interatomic potentials (MLIPs), especially in ionic, polar and interf…
Accelerating Molecular Dynamics Simulations using Fast Ewald Summation with Prolates
Jiuyang Liang, Libin Lu, Alex Barnett +2
The evaluation of long-range Coulomb interactions is a significant cost in molecular dynamics (MD), even when using Particle Mesh Ewald (PME) or Particle-Particle-Particle-Mesh (PP…
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…
Fast Ewald Summation with Prolates for Charged Systems in the NPT Ensemble
Jiuyang Liang, Libin Lu, Shidong Jiang
We present an NPT extension of Ewald summation with prolates (ESP), a spectrally accurate and scalable particle-mesh method for molecular dynamics simulations of periodic, charged…
Random Batch Sum-of-Gaussians Method for Molecular Dynamics of Born-Mayer-Huggins Systems
Chen Chen, Jiuyang Liang, Zhenli Xu +1
The Born-Mayer-Huggins (BMH) potential, which combines Coulomb interactions with dispersion and short-range exponential repulsion, is widely used for ionic materials such as molten…