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Verfasst von:Yen, Steffi Xiang-Ting [VerfasserIn]   i
 Reffert, Sabine [VerfasserIn]   i
 Schilbach, Elena [VerfasserIn]   i
 Röser, Siegfried [VerfasserIn]   i
 Kharchenko, Nina V. [VerfasserIn]   i
 Piskunov, Anatoly E. [VerfasserIn]   i
Titel:Reanalysis of nearby open clusters using gaia DR1/TGAS and HSOY
Verf.angabe:Steffi X. Yen, Sabine Reffert, Elena Schilbach, Siegfried Röser, Nina V. Kharchenko, and Anatoly E. Piskunov
E-Jahr:2018
Jahr:06 July 2018
Umfang:21 S.
Fussnoten:Gesehen am 05.03.2019
Titel Quelle:Enthalten in: Astronomy and astrophysics
Ort Quelle:Les Ulis : EDP Sciences, 1969
Jahr Quelle:2018
Band/Heft Quelle:615(2018) Artikel-Nummer A12, 21 Seiten
ISSN Quelle:1432-0746
Abstract:<i>Context<i/>. Open clusters have long been used to gain insights into the structure, composition, and evolution of the Galaxy. With the large amount of stellar data available for many clusters in the <i>Gaia<i/> era, new techniques must be developed for analyzing open clusters, as visual inspection of cluster color-magnitude diagrams is no longer feasible. An automatic tool will be required to analyze large samples of open clusters.<i>Aims<i/>. We seek to develop an automatic isochrone-fitting procedure to consistently determine cluster membership and the fundamental cluster parameters.<i>Methods<i/>. Our cluster characterization pipeline first determined cluster membership with precise astrometry, primarily from TGAS and HSOY. With initial cluster members established, isochrones were fitted, using a χ<sup>2<sup/> minimization, to the cluster photometry in order to determine cluster mean distances, ages, and reddening. Cluster membership was also refined based on the stellar photometry. We used multiband photometry, which includes ASCC-2.5 <i>BV<i/>, 2MASS <i>JHK<sub>s<sub/><i/>, and <i>Gaia G<i/> band.<i>Results<i/>. We present parameter estimates for all 24 clusters closer than 333 pc as determined by the Catalogue of Open Cluster Data and the Milky Way Star Clusters catalog. We find that our parameters are consistent to those in the Milky Way Star Clusters catalog.<i>Conclusions<i/>. We demonstrate that it is feasible to develop an automated pipeline that determines cluster parameters and membership reliably. After additional modifications, our pipeline will be able to use <i>Gaia<i/> DR2 as input, leading to better cluster memberships and more accurate cluster parameters for a much larger number of clusters.
DOI:doi:10.1051/0004-6361/201731905
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: http://dx.doi.org/10.1051/0004-6361/201731905
 DOI: https://doi.org/10.1051/0004-6361/201731905
Datenträger:Online-Ressource
Sprache:eng
K10plus-PPN:1588336263
Verknüpfungen:→ Zeitschrift

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