Removing Reddening to Enhance Gaia's XP Spectra Clustering

Reddening, or extinction, distorts stellar spectra due to dust between the source and the observer, in this case, the Gaia satellite. It shifts energy from the blue to the red part of a spectrum, potentially confusing hot, reddened stars with cooler ones, since the cooler the star, the higher the SED at the red part. Gaia currently provides 2D extinction values, which can lead to errors for nearby stars, where a 3D model would be ideal. Our research group clusters Gaia sources using SOM maps, taking into account only their XP spectra. To improve our results, we are developing AI methods to remove extinction using denoising autoencoders and disentangling techniques trained on spectra with similar astrophysical parameters but different extinction levels.

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Publication Details

Published
2024-11-01
DOI
https://doi.org/10.17979/spudc.9788497498913.19
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Removing Reddening to Enhance Gaia's XP Spectra Clustering

R. Santoveña, Carlos Dafonte, L. Pallas-Quintela, M. Manteiga et al.
Distributed and Parallel Computing Systems
article

Removing Reddening to Enhance Gaia's XP Spectra Clustering

R. Santoveña, Carlos Dafonte, L. Pallas-Quintela, M. Manteiga, D. Garabato, Ángel Regueiro
article en

Abstract

Reddening, or extinction, distorts stellar spectra due to dust between the source and the observer, in this case, the Gaia satellite. It shifts energy from the blue to the red part of a spectrum, potentially confusing hot, reddened stars with cooler ones, since the cooler the star, the higher the SED at the red part. Gaia currently provides 2D extinction values, which can lead to errors for nearby stars, where a 3D model would be ideal. Our research group clusters Gaia sources using SOM maps, taking into account only their XP spectra. To improve our results, we are developing AI methods to remove extinction using denoising autoencoders and disentangling techniques trained on spectra with similar astrophysical parameters but different extinction levels.

European Space Agency, European Commission, Xunta de Galicia, HORIZON EUROPE Framework Programme, European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 68%
Distributed and Parallel Computing Systems
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Removing Reddening to Enhance Gaia's XP Spectra Clustering — R. Santoveña, Carlos Dafonte, et al. · (2024) | TGRS Research Map | TGRS