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20242026
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physics.flu-dyn2026

Gappy Reconstruction of Bubbly Flows by Guided Diffusion Models

Hridey Narula, Tianyi Li, Michele Buzzicotti +2

Experiments in multiphase flows are often limited in their ability to simultaneously obtain velocity measurements in different phases. At the same time, flow reconstruction from ph…

physics.flu-dyn2026

Stochastic Multiscale Reconstruction of Lagrangian Turbulence via Guided Diffusion Models

Conghui Wang, Tianyi Li, Luca Biferale +3

Lagrangian turbulence is characterized by intermittent, fat-tailed fluctuations and nontrivial correlations across temporal scales, making a quantitative description of its full mu…

physics.flu-dyn2026

Turbulent pair dispersion with Stochastic Generative Diffusion Models

Andrei Pantea, Luca Biferale, Michele Buzzicotti +3

Recent advances in data-driven modeling have shown that diffusion models can successfully generate synthetic Lagrangian trajectories in turbulent flows. Building on this progress,…

physics.flu-dyn2026

Physics-Constrained Diffusion Model for Synthesis of 3D Turbulent Data

Tianyi Li, Michele Buzzicotti, Fabio Bonaccorso +1

Synthesizing fully developed three-dimensional turbulent velocity fields remains a long-standing problem in fluid mechanics and an open challenge for generative modeling. The diffi…

physics.flu-dyn2025

Deterministic diffusion models for Lagrangian turbulence: robustness and encoding of extreme events

Tianyi Li, Flavio Tuteri, Michele Buzzicotti +2

Modeling Lagrangian turbulence remains a fundamental challenge due to its multiscale, intermittent, and non-Gaussian nature. Recent advances in data-driven diffusion models have en…

physics.flu-dyn2025

Generation of cosmic ray trajectories by a Diffusion Model trained on test particles in 3D magnetohydrodynamic turbulence

Johannes Martin, Jeremiah Lübke, Tianyi Li +3

Models for the transport of high energy charged particles through strong magnetic turbulence play a key role in space and astrophysical studies, such as describing the propagation…