3 papers
physics.flu-dyn2026
Exact coherent structures as building blocks of turbulence on large domains
Dmitriy Zhigunov, Jacob Page
Exact unstable solutions of the Navier-Stokes equations are thought to underpin the dynamics of turbulence, but are usually computed in minimal computational domains. Here, we exte…
physics.flu-dyn2025
Characterizing the Reynolds number dependence of the chaotic attractor in two-dimensional turbulence with dimension-minimizing autoencoders
Andrew Cleary, Jacob Page
Deep autoencoder neural networks can generate highly accurate, low-order representations of turbulence. We design a new family of autoencoders which are a combination of a 'dense-b…
physics.flu-dyn2025
Dynamical relevance of periodic orbits under increasing Reynolds number and connections to inviscid dynamics
Andrew Cleary, Jacob Page
Large numbers of relative periodic orbits (RPOs) have been found recently in doubly-periodic, two-dimensional Kolmogorov flow at moderate Reynolds numbers . Whi…