Physical Dynamic

Physical dynamics research focuses on developing computational models that accurately predict and understand the movement and interaction of objects, encompassing both rigid and deformable bodies, and extending to complex systems like fluids. Current efforts concentrate on improving model generalization across diverse materials and scenarios, employing architectures like graph neural networks and incorporating physical priors such as conservation laws and Hamiltonian structures to enhance accuracy and interpretability. These advancements are crucial for improving robotic manipulation, simulating complex physical phenomena, and enhancing the safety and security of cyber-physical systems by enabling more robust anomaly detection.