Reanalysis of 24 nearby open clusters using Gaia data
We have developed a fully automated cluster characterization pipeline, which simultaneously determines cluster membership and fits the fundamental cluster parameters: distance, reddening, and age. We present results for 24 established clusters and compare them to literature values. Given the large a...
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| Hauptverfasser: | , , , , , |
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| Dokumenttyp: | Article (Journal) Konferenzschrift |
| Sprache: | Englisch |
| Veröffentlicht: |
07 March 2018
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| In: |
Proceedings of the International Astronomical Union
Year: 2017, Jahrgang: 12, Heft: S330, Pages: 281-282 |
| ISSN: | 1743-9221 |
| DOI: | 10.1017/S1743921317006366 |
| Online-Zugang: | Verlag, Volltext: https://doi.org/10.1017/S1743921317006366 Verlag, Volltext: https://www.cambridge.org/core/journals/proceedings-of-the-international-astronomical-union/article/reanalysis-of-24-nearby-open-clusters-using-gaia-data/8BB097E2BD60B3EE2ACE1D4B734FC3A7 
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| Verfasserangaben: | Steffi X. Yen, Sabine Reffert, Siegfried Röser, Elena Schilbach, Nina V. Kharchenko and Anatoly E. Piskunov |
| Zusammenfassung: | We have developed a fully automated cluster characterization pipeline, which simultaneously determines cluster membership and fits the fundamental cluster parameters: distance, reddening, and age. We present results for 24 established clusters and compare them to literature values. Given the large amount of stellar data for clusters available from Gaia DR2 in 2018, this pipeline will be beneficial to analyzing the parameters of open clusters in our Galaxy. |
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| Beschreibung: | Gesehen am 16.02.2021 |
| Beschreibung: | Online Resource |
| ISSN: | 1743-9221 |
| DOI: | 10.1017/S1743921317006366 |