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Title

Stellar open clusters' membership probabilities: An N-dimensional geometrical approach

AuthorsSampedro, Laura ; Alfaro, Emilio J.
KeywordsOpen cluster and associations: individual: NGC 2682
Open cluster and associations: general
Astrometry
Methods: data analysis
Methods: numerical
methods: Statistical
Issue Date2016
PublisherOxford University Press
CitationMonthly Notices of the Royal Astronomical Society 457(4): 3949- 3962 (2016)
AbstractWe present a new geometrical method aimed at determining the members of open clusters. The methodology estimates, in an N-dimensional space, the membership probabilities by means of the distances between every star and the cluster central overdensity. It can handle different sets of variables, which have to satisfy the simple condition of being more densely distributed for the cluster members than for the field stars (as positions, proper motions, radial velocities and/or parallaxes are). Unlike other existing techniques, this fact makes the method more flexible and so can be easily applied to different data sets. To quantify how the method identifies the cluster members, we design series of realistic simulations recreating sky regions in both position and proper motion subspaces populated by clusters and field stars. The results, using different simulated data sets (N = 1, 2 and 4 variables), show that the method properly recovers a very high fraction of simulated clustermembers, with a low number of misclassified stars. To compare the goodness of our methodology, we also run other existing algorithms on the same simulated data. The results show that our method has a similar or even better performance than the other techniques. We study the robustness of the new methodology from different subsamplings of the initial sample, showing a progressive deterioration of the capability of our method as the fraction of missing objects increases. Finally, we apply all the methodologies to the real cluster NGC 2682, indicating that our methodology is again in good agreement with preceding studies.
URIhttp://hdl.handle.net/10261/135405
DOI10.1093/mnras/stw243
Identifiersdoi: 10.1093/mnras/stw243
issn: 1365-2966
Appears in Collections:(IAA) Artículos
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