Software underlying the publication: State space approach to identify precursors to extreme events in turbulence
4TU.ResearchDatavia 4TU.ResearchData (via DataCite) · updated 29 October 2026
What's in it
Code for reproducing: State space approach to identify precursors to extreme events in turbulence : K. R. Schuurman, R. P. Dwight, N. A. K. Doan. This research identifies precursors to extreme events using a data-driven methodology that employs a symmetry-reduced latent space representation and log-likelihood classification. This methodology identifies specific modes in a flow that correlate with the precursors, thereby increasing understanding of the physics. Four numbered scripts reproduce the main results for latent dimension n_d = 8. Run them in order from this folder. All shared code is in kolmogorov_lib.py . The flow solver is not included; the scripts start from the stored trajectories.
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