Published April 24, 2025
| Version v1
Data paper
Open
Rayleigh-Bénard convection data for publication "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
Description
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.
Files
Rayleigh-Benard-all-data.zip
Files
(9.9 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:f51519b9f2ba7f44f020ee2fcaf54040
|
9.9 GB | Preview Download |
Additional details
Software
- Repository URL
- https://github.com/katiana22/latent-deeponet
- Programming language
- Python