Photometric and kinematic studies of open clusters Ruprecht 1 and Ruprecht 171
Hikmet \c{C}akmak, Talar Yontan, Sel\c{c}k Bilir, Timothy S. Banks,, Ra\'ul. Michel, Esin Soydugan, Seliz Ko\c{c}, H\"ulya Er\c{c}ay

TL;DR
This paper provides a comprehensive photometric and kinematic analysis of open clusters Ruprecht 1 and Ruprecht 171, determining their fundamental parameters, membership, metallicities, ages, distances, and orbital origins using CCD UBV and Gaia DR3 data.
Contribution
It offers new detailed astrophysical parameters and membership probabilities for Ruprecht 1 and Ruprecht 171 based on combined UBV and Gaia data, including their potential formation outside the solar circle.
Findings
Ruprecht 1 has a color excess E(B-V)=0.166 mag and age ~580 Myr.
Ruprecht 171 has a color excess E(B-V)=0.301 mag and age ~2700 Myr.
Both clusters likely formed outside the solar circle.
Abstract
This study outlines a detailed investigation using CCD {\it UBV} and {\it Gaia} DR3 data sets of the two open clusters Ruprecht 1 (Rup-1) and Ruprecht 171 (Rup-171). Fundamental astrophysical parameters such as color excesses, photometric metallicities, ages, and isochrone distances were based on {\it UBV}-data analyses, whereas membership probability calculations, structural and astrophysical parameters, as well as the kinematic analyses were based on {\it Gaia} DR3-data. We identified 74 and 596 stars as the most probable cluster members with membership probabilities over 50\% for Rup-1 and Rup-171, respectively. The color excesses were obtained as and mag for Rup-1 and Rup-171, respectively. Photometric metallicity analyses were performed by considering F-G type main-sequence member stars and found to be [Fe/H]= and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
Topics3D Modeling in Geospatial Applications · demographic modeling and climate adaptation
