Reanalysis of nearby open clusters using Gaia DR1/TGAS and HSOY^⋆

¹ Zentrum für Astronomie der Universität Heidelberg, Landessternwarte, Königstuhl 12, 69117 Heidelberg, Germany
e-mail: syen@lsw.uni-heidelberg.de
² Zentrum für Astronomie der Universität Heidelberg, Astronomisches Rechen-Institut, Mönchhofstrasse 12-14, 69120 Heidelberg, Germany
³ Main Astronomical Observatory, 27 Academica Zabolotnogo Str., 03143 Kiev, Ukraine
⁴ Institute of Astronomy of the Russian Acad. Sci., 48 Pyatnitskaya Str., 109017 Moscow, Russia

Received: 6 September 2017
Accepted: 18 January 2018

Abstract

Context. 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 Gaia 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.

Aims. We seek to develop an automatic isochrone-fitting procedure to consistently determine cluster membership and the fundamental cluster parameters.

Methods. 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 χ² 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 BV, 2MASS JHK_s, and Gaia G band.

Results. 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.

Conclusions. 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 Gaia DR2 as input, leading to better cluster memberships and more accurate cluster parameters for a much larger number of clusters.