Cluster membership analysis with supervised learning and N-body simulations
Bissekenov A. Kalambay M. Abdikamalov E. Pang X. Berczik P. Shukirgaliyev B.
1 September 2024EDP Sciences
Astronomy and Astrophysics
2024#689
Context. Membership analysis is an important tool for studying star clusters. There are various approaches to membership determination, including supervised and unsupervised machine-learning (ML) methods. Aims. We perform membership analysis using the supervised ML approach. Methods. We trained and tested our ML models on two sets of star cluster data: snapshots from N-body simulations, and 21 different clusters from the Gaia Data Release 3 data. Results. We explored five different ML models: random forest (RF), decision trees, support vector machines, feed-forward neural networks, and K-nearest neighbors. We find that all models produce similar results, and the accuracy of RF is slightly better. We find that a balance of classes in the datasets is optional for a successful learning. The classification accuracy strongly depends on the astrometric parameters. The addition of photometric parameters does not improve the performance. We find no strong correlation between the classification accuracy and the cluster age, mass, and half-mass radius. At the same time, models trained on clusters with a larger number of members generally produce better results.
Galaxy: kinematics and dynamics , methods: data analysis , methods: numerical , open clusters and associations: general , solar neighborhood
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Department of Physics, Xi’an Jiaotong-Liverpool University, 111 Ren’ai Road, Dushu Lake Science and Education Innovation District, Jiangsu Province, Suzhou, 215123, China
Energetic Cosmos Laboratory, Nazarbayev University, 53 Kabanbay Batyr Ave., Astana, 010000, Kazakhstan
Heriot-Watt University Aktobe Campus, 263 Zhubanov Brothers Str, Aktobe, 030000, Kazakhstan
Heriot-Watt International Faculty, K. Zhubanov Aktobe Regional University, 263 Zhubanov Brothers Str, Aktobe, 030000, Kazakhstan
Fesenkov Astrophysical Institute, 23 Observatory Str., Almaty, 050020, Kazakhstan
Faculty of Physics and Technology, Al-Farabi Kazakh National University, 71 Al-Farabi Ave, Almaty, 050020, Kazakhstan
Department of Physics, School of Sciences and Humanities, Nazarbayev University, 53 Kabanbay Batyr Ave., Astana, 010000, Kazakhstan
Shanghai Key Laboratory for Astrophysics, Shanghai Normal University, 100 Guilin Road, Shanghai, 200234, China
Nicolaus Copernicus Astronomical Centre Polish Academy of Sciences, ul. Bartycka 18, Warsaw, 00-716, Poland
Konkoly Observatory, HUN-REN Research Centre for Astronomy and Earth Sciences, Konkoly Thege Miklós út 15–17, Budapest, 1121, Hungary
Main Astronomical Observatory, National Academy of Sciences of Ukraine, 27 Akademika Zabolotnoho St., Kyiv, 03143, Ukraine
Department of Physics
Energetic Cosmos Laboratory
Heriot-Watt University Aktobe Campus
Heriot-Watt International Faculty
Fesenkov Astrophysical Institute
Faculty of Physics and Technology
Department of Physics
Shanghai Key Laboratory for Astrophysics
Nicolaus Copernicus Astronomical Centre Polish Academy of Sciences
Konkoly Observatory
Main Astronomical Observatory
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