Millions of Main-Sequence Binary Stars from Gaia BP/RP Spectra
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909989342281728 |
|---|---|
| author | Li, Jiadong Rix, Hans-Walter Ting, Yuan-Sen Müller-Horn, Johanna El-Badry, Kareem Liu, Chao Seeburger, Rhys Green, Gregory M. Zhang, Xiangyu |
| author_facet | Li, Jiadong Rix, Hans-Walter Ting, Yuan-Sen Müller-Horn, Johanna El-Badry, Kareem Liu, Chao Seeburger, Rhys Green, Gregory M. Zhang, Xiangyu |
| contents | We present the main-sequence binary (MSMS) Catalog derived from Gaia Data Release 3 BP/RP (XP) spectra. Leveraging the vast sample of low-resolution Gaia XP spectra, we develop a forward modeling approach that maps stellar mass and photometric metallicity to XP spectra using a neural network. Our methodology identifies binary systems through statistical comparison of single- and binary-star model fits, enabling detection of binaries with mass ratios between 0.4 and 1.0 and flux ratios larger than 0.1. From an initial sample of 35 million stars within 1 kpc, we identify 14 million binary candidates and define a high-confidence "golden sample" of 1 million binary systems. This large, homogeneous sample enables detailed statistical analysis of binary properties across diverse Galactic environments, providing new insights into binary star formation and evolution. In addition, the $χ^2$ comparison allows us to distinguish stars with luminous companions from single stars or binaries with dark companions, such as white dwarfs, neutron stars and black hole candidates, improving our understanding of compact object populations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_09622 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Millions of Main-Sequence Binary Stars from Gaia BP/RP Spectra Li, Jiadong Rix, Hans-Walter Ting, Yuan-Sen Müller-Horn, Johanna El-Badry, Kareem Liu, Chao Seeburger, Rhys Green, Gregory M. Zhang, Xiangyu Solar and Stellar Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics We present the main-sequence binary (MSMS) Catalog derived from Gaia Data Release 3 BP/RP (XP) spectra. Leveraging the vast sample of low-resolution Gaia XP spectra, we develop a forward modeling approach that maps stellar mass and photometric metallicity to XP spectra using a neural network. Our methodology identifies binary systems through statistical comparison of single- and binary-star model fits, enabling detection of binaries with mass ratios between 0.4 and 1.0 and flux ratios larger than 0.1. From an initial sample of 35 million stars within 1 kpc, we identify 14 million binary candidates and define a high-confidence "golden sample" of 1 million binary systems. This large, homogeneous sample enables detailed statistical analysis of binary properties across diverse Galactic environments, providing new insights into binary star formation and evolution. In addition, the $χ^2$ comparison allows us to distinguish stars with luminous companions from single stars or binaries with dark companions, such as white dwarfs, neutron stars and black hole candidates, improving our understanding of compact object populations. |
| title | Millions of Main-Sequence Binary Stars from Gaia BP/RP Spectra |
| topic | Solar and Stellar Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2507.09622 |