A new approach to magnify wave functions when imaging interacting ultracold atoms

The precise imaging of many-body systems, which are comprised of many interacting particles, can help to validate theoretical ...
IEEE

Spatio-Temporal Graph Convolutional Neural Networks for Physics-Aware Grid Learning Algorithms

Abstract: This paper proposes novel architectures for spatio-temporal graph convolutional and recurrent neural networks whose structure is inspired by the physics of power systems. The key insight ...
IEEE

Physics-Data Hybrid Driven Edge-Featured Graph Attention Networks for Surface Currents Learning of 3D PEC Targets

Abstract: To achieve fast and accurate modeling of electrically large targets, this paper proposes a physics-data hybrid driven surface current learning method (PdEgatSCL), which can learn combined ...