Nature

Molecular dynamics articles from across Nature Portfolio

Molecular dynamics is a method that uses Newton’s equations of motion to computationally simulate the time evolution of a set of interacting atoms. Such techniques are dependent on a description of ...
IEEE

Group Point Symmetry and Multi-Step Dynamics Prediction for Physical Systems with Graph Neural Networks

Abstract: Modeling the 3D dynamics of relational systems is a key challenge in the field of natural sciences, especially in molecular simulations and particle mechanics. However, existing graph neural ...
IEEE

Predicting Dynamics on Hypergraphs with Graph Attention Networks

Abstract: Hypergraphs offer a more effective approach to modeling virus spread by capturing higher-order interactions among individuals, yet accurately predicting dynamics on hypergraphs remains a ...
GitHub

Graph Neural Network (GNN) simulator for particle dynamics in PyTorch; Extension to generate a custom gravitational N-body dataset using classical numerical integrators.

Inspired by Stanford CS224W blog post: https://medium.com/stanford-cs224w/simulating-complex-physics-with-graph-networks-step-by-step-177354cb9b05 A minimal project ...