LarsDoorenbos/generate-spectra
Repository for "Galaxy spectroscopy without spectra: Galaxy properties from photometric images with conditional diffusion models" (ApJ) and "Generating astronomical spectra from photometry with conditional diffusion models" (ML4PS@NeurIPS 2022)
This project helps astronomers and astrophysicists predict detailed optical galaxy spectra from broad-band photometric images. By inputting multi-band galaxy images, it generates spectroscopic data, allowing for the derivation of galaxy properties like metallicity, age, and velocity dispersion without needing actual spectroscopic observations. It is designed for researchers studying galaxy evolution and cosmic structures.
No commits in the last 6 months.
Use this if you need to infer detailed galaxy properties from large photometric surveys where spectroscopic data is scarce or unavailable.
Not ideal if you already have extensive spectroscopic data or require very high-resolution, observed spectra for specific, targeted analyses.
Stars
14
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2
Language
Python
License
MIT
Category
Last pushed
Apr 10, 2025
Commits (30d)
0
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