Rayleigh-Bénard convection data for publication "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
This dataset contains the full set of Rayleigh–Bénard convection simulations generated using the Dedalus spectral solver, as described in the Nature Communications article titled "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems." These simulations were used to train and validate the latent neural operator framework introduced in the paper.
Institutions
- Johns Hopkins University (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-04-24
- DOI
- https://doi.org/10.5281/zenodo.15276383
- Primary Topic
- Model Reduction and Neural Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00