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China Space Station Telescope and Variable Star Studies

Published online by Cambridge University Press:  06 February 2024

Xiaodian Chen*
Affiliation:
CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China School of Astronomy and Space Science, University of the Chinese Academy of Sciences, Beijing, China Department of Astronomy, China West Normal University, Nanchong 637009, China
Shu Wang
Affiliation:
CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China School of Astronomy and Space Science, University of the Chinese Academy of Sciences, Beijing, China Department of Astronomy, China West Normal University, Nanchong 637009, China
Licai Deng
Affiliation:
CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China School of Astronomy and Space Science, University of the Chinese Academy of Sciences, Beijing, China Department of Astronomy, China West Normal University, Nanchong 637009, China
Richard de Grijs
Affiliation:
School of Mathematical and Physical Sciences, Macquarie University, Balaclava Road, Sydney, NSW 2109, Australia Astrophysics and Space Technologies Research Centre, Macquarie University, Balaclava Road, Sydney, NSW 2109, Australia
Xiaoyue Zhou
Affiliation:
CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China
Xiaohan Chen
Affiliation:
CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China
Jianxing Zhang
Affiliation:
CAS Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing, China
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Abstract

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In the last five years, the number of periodic variable stars has increased by two million. We used the ZTF DR2 data to find and build a catalog that includes 780,000 periodic variable stars. These periodic variable stars were classified into 11 types, which greatly complemented the variable stars in Galactic disk. Based on the latest ZTF DR16 data, we found 2 million variable candidates. We trained a machine learner to classify variable stars, and the learner had a prediction accuracy of 94%. Using millions of variable stars, we carried out studies to optimize the period–luminosity relations and the Galactic structure and the extinction law. With the future China Space Station Telescope, millions of variable stars in the Local Group will be discovered. They help to study the structure of our Local Group and also to cross-check the distance ladders based on different variable stars.

Type
Contributed Paper
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of International Astronomical Union

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