Millions of main-sequence binary stars from

We present an extensive catalog of likely main-sequence main-sequence (MSMS) binary stars systems derived from Gaia Data Release 3 BP/RP (XP) spectra through the comparison of single- and binary-star model fits. Leveraging the large sample of low-resolution Gaia XP spectra, we used a neural network to build a forward model for spectral luminosities of single stars as a function of stellar mass and photometric metallicity. Applying this model to XP spectra, we found that this model enables the identification of binaries with mass ratios between 0.5 and 1.0 and flux ratios larger than 0.1 as “poor” fits to the data, either in spectral shape or flux normalization. From an initial sample of 35 million stars within 1 kpc, we identified 14 million possible binary candidates, and a high-confidence “golden sample” of 1 million binary systems. This large homogeneous sample of spectrophotometry-based binaries enables population studies of luminous MSMS binaries and – in conjunction with kinematic or astrometric probes – permits identification of binaries with dark or dim companions, such as white dwarfs, neutron star and black hole candidates, improving our understanding of compact object populations.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-12-09
DOI
https://doi.org/10.1051/0004-6361/202556362/pdf
Primary Topic
Stellar, planetary, and galactic studies
Type
article
Field-Weighted Citation Impact
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article

Millions of main-sequence binary stars from

Rhys Seeburger, Kareem J. El-Badry, Gregory Green, Johanna Müller-Horn et al.
Springer Link (Chiba Institute of Technology)
Stellar, planetary, and galactic studies
article

Millions of main-sequence binary stars from

Rhys Seeburger, Kareem J. El-Badry, Gregory Green, Johanna Müller-Horn, XiangYu ZHANG, Hans-Walter Rix, Chao Liu
article en

Abstract

We present an extensive catalog of likely main-sequence main-sequence (MSMS) binary stars systems derived from Gaia Data Release 3 BP/RP (XP) spectra through the comparison of single- and binary-star model fits. Leveraging the large sample of low-resolution Gaia XP spectra, we used a neural network to build a forward model for spectral luminosities of single stars as a function of stellar mass and photometric metallicity. Applying this model to XP spectra, we found that this model enables the identification of binaries with mass ratios between 0.5 and 1.0 and flux ratios larger than 0.1 as “poor” fits to the data, either in spectral shape or flux normalization. From an initial sample of 35 million stars within 1 kpc, we identified 14 million possible binary candidates, and a high-confidence “golden sample” of 1 million binary systems. This large homogeneous sample of spectrophotometry-based binaries enables population studies of luminous MSMS binaries and – in conjunction with kinematic or astrometric probes – permits identification of binaries with dark or dim companions, such as white dwarfs, neutron star and black hole candidates, improving our understanding of compact object populations.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 28%
Stellar, planetary, and galactic studies
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Millions of main-sequence binary stars from — Rhys Seeburger, Kareem J. El-Badry, et al. · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS