Li, Jia-jia https://orcid.org/0009-0009-7824-5984
Xiong, Jian-ping https://orcid.org/0000-0003-4829-6245
Tian, Zhi-jia https://orcid.org/0000-0003-0220-7112
Liu, Chao https://orcid.org/0000-0002-1802-6917
Han, Zhan-wen https://orcid.org/0000-0001-9204-7778
Chen, Xue-fei https://orcid.org/0000-0001-5284-8001
Funding for this research was provided by:
MOST ∣ National Natural Science Foundation of China (12288102)
National Key R&D Program of China (2021YFA1600403)
Yunnan Fundamental Research Projects (202201BC070003)
International Centre of Supernovae, Yunnan Key Laboratory (202302AN360001)
Yunnan Revitalization Talent Support Program - Science & Technology Champion Project (202305AB350003)
China Manned Space Project (CMS-CSST-2021-A10)
Article Title: Identify Main-sequence Binaries from the Chinese Space Station Telescope Survey with Machine Learning. II. Based on Gaia and GALEX
Journal Title: The Astronomical Journal
Article Type: paper
Copyright Information: © 2025. The Author(s). Published by the American Astronomical Society.
Publication dates
Date Received: 2024-12-19
Date Accepted: 2025-02-20
Online publication date: 2025-03-21