Generative Diffusion Models for Synthetic High-Fidelity Lagrangian Turbulence Data

A machine learning approach based on state-of-the-art diffusion models can generate single-particle trajectories in three-dimensional turbulence at high Reynolds numbers, accurately reproducing the statistical and topological properties exhibited by particle trajectories in turbulence.