Synthetic Lagrangian Turbulence by Generative Diffusion Models

arXiv:2307.08529v2 Announce Type: replace-cross
Abstract: Lagrangian turbulence lies at the core of numerous applied and fundamental problems related to the physics of dispersion and mixing in engineering, bio-fluids, atmosphere, oceans, and astrophysics. Despite exceptional theoretical, numerical, and experimental efforts conducted over the past thirty years, no existing models are capable of faithfully reproducing statistical and topological properties exhibited by particle trajectories in turbulence. We propose a machine learning approach, based on a state-of-the-art diffusion model, to generate single-particle trajectories in …

abstract arxiv astrophysics atmosphere bio cond-mat.stat-mech core cs.ce cs.lg diffusion diffusion models engineering experimental fundamental generative lies nlin.cd numerical oceans physics physics.flu-dyn synthetic turbulence type