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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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Bibliographic Details
Main Authors: Yen, Steffi Xiang-Ting (Author) , Reffert, Sabine (Author) , Röser, Siegfried (Author) , Schilbach, Elena (Author) , Kharchenko, Nina V. (Author) , Piskunov, Anatoly E. (Author)
Format: Article (Journal) Conference Paper
Language:English
Published: 07 March 2018
In: Proceedings of the International Astronomical Union
Year: 2017, Volume: 12, Issue: S330, Pages: 281-282
ISSN:1743-9221
DOI:10.1017/S1743921317006366
Online Access: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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Author Notes:Steffi X. Yen, Sabine Reffert, Siegfried Röser, Elena Schilbach, Nina V. Kharchenko and Anatoly E. Piskunov
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Summary: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.
Item Description:Gesehen am 16.02.2021
Physical Description:Online Resource
ISSN:1743-9221
DOI:10.1017/S1743921317006366

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