University of Hertfordshire

From the same journal

From the same journal

By the same authors


  • K. Peña Ramírez
  • L. C. Smith
  • S. Ramírez Alegría
  • A. -N. Chené
  • C. González-Fernández
  • P. W. Lucas
  • D. Minniti
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Original languageEnglish
Pages (from-to)5799-5813
JournalMonthly Notices of the Royal Astronomical Society
Publication statusPublished - 11 May 2022


Open clusters are key coeval structures that help us understand star formation, stellar evolution and trace the physical properties of our Galaxy. In the past years, the isolation of open clusters from the field has been heavily alleviated by the access to accurate large-scale stellar parallaxes and proper motions along a determined line of sight. Still, there are limitations regarding their completeness since large-scale studies rely on optical wavelengths. Here we extend the open clusters sequences towards fainter magnitudes complementing the Gaia photometric and astrometric information with near-infrared data from the VVV survey. We performed a homogeneous analysis on 37 open clusters implementing two coarse-to-fine characterization methods: extreme deconvolution Gaussian mixture models coupled with an unsupervised machine learning method on 8-dimensional parameter space. The process allowed us to separate the clusters from the field at near-infrared wavelengths. We report an increase of ~47% new member candidates on average in our sample (considering only sources with high membership probability p$\geqq$0.9). This study is the second in a series intended to reveal open cluster near-infrared sequences homogeneously.


16 pages. 5 figures. MNRAS accepted. v2: language edits and references updated at the proof stage; arXiv admin note: text overlap with arXiv:2102.04303

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