Generating astronomical spectra from photometry with conditional diffusion models

A trade-off between speed and information controls our understanding of astronomical objects. Fast-to-acquire photometric observations provide global properties, while costly and time-consuming spectroscopic measurements enable a better understanding of the physics governing their evolution. Here, w...

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Bibliographic Details
Published in:arXiv.org 2022-11
Main Authors: Doorenbos, Lars, Cavuoti, Stefano, Longo, Giuseppe, Brescia, Massimo, Sznitman, Raphael, Márquez-Neila, Pablo
Format: Article
Language:English
Subjects:
Astronomical models
Celestial bodies
Diffusion rate
Image acquisition
Photometry
Spectra
Online Access:Get full text
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Summary:A trade-off between speed and information controls our understanding of astronomical objects. Fast-to-acquire photometric observations provide global properties, while costly and time-consuming spectroscopic measurements enable a better understanding of the physics governing their evolution. Here, we tackle this problem by generating spectra directly from photometry, through which we obtain an estimate of their intricacies from easily acquired images. This is done by using multi-modal conditional diffusion models, where the best out of the generated spectra is selected with a contrastive network. Initial experiments on minimally processed SDSS galaxy data show promising results.
ISSN:2331-8422