Particle System

Particle systems research focuses on understanding and modeling the collective behavior of numerous interacting entities, aiming to predict their overall dynamics from individual interactions. Current research emphasizes developing efficient algorithms, such as those based on optimal transport, material point methods, and smoothed particle hydrodynamics, to simulate and infer properties of these systems, often leveraging machine learning techniques like graph neural networks and variational inference. These advancements have significant implications for diverse fields, including statistical physics, materials science, and machine learning, enabling more accurate simulations and improved understanding of complex systems.