SM-Net: A Learned Continuous Spectral Manifold from Multiple Stellar Libraries
Authors/Creators
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1.
University of Western Australia
Contributors
Contact person:
Project manager:
Researcher (2):
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1.
University of Western Australia
Description
This record contains the trained SM-Net “lookup” model weights used by the SM-Net local Dash/Plotly web interface for rapid synthetic stellar spectrum generation from (Teff,logg,logZ). The weights correspond to models trained on a combined grid spanning the PHOENIX–Husser, C3K–Conroy, TMAP–Werner, and OB–PoWR libraries.
These files are intended to be used with the open-source SM-Net repository (installation instructions and the local web interface are provided there):
https://github.com/ICRAR/SM_Net
The repository ships lightweight metadata caches (*.meta.npz) for parameter bounds and wavelength grids; this Zenodo deposit provides the large binary weight archives required to run the models.
DOI: 10.5281/zenodo.18883385
Recommended citation: cite this Zenodo record for the weights and the GitHub repository for the code and interface.
Files
Files
(19.5 GB)
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Additional details
Dates
- Submitted
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2026-03-06
Software
- Repository URL
- https://github.com/ICRAR/SM_Net
- Programming language
- Python