English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

We present a study of six open clusters (Berkeley 67, King 2, NGC 2420, NGC2477, NGC 2682 and NGC 6940) using the Ultra Violet Imaging Telescope (UVIT)aboard \textit{ASTROSAT} and \textit{Gaia} EDR3. We used combinations ofastrometric, photometric and systematic parameters to train and supervise amachine learning algorithm along with a Gaussian mixture model for thedetermination of cluster membership. This technique is robust, reproducible andversatile in various cluster environments. In this study, the \textit{Gaia}EDR3 membership catalogues are provided along with classification of the starsas \texttt{members, candidates} and \texttt{field} in the six clusters. Wecould detect 200--2500 additional members using our method with respect toprevious studies, which helped estimate mean space velocities, distances,number of members and core radii. UVIT photometric catalogues, which includeblue stragglers, main-sequence and red giants are also provided. FromUV--Optical colour-magnitude diagrams, we found that majority of the sources inNGC 2682 and a few in NGC 2420, NGC 2477 and NGC 6940 showed excess UV flux.NGC 2682 images have ten white dwarf detection in far-UV. The far-UV andnear-UV images of the massive cluster NGC 2477 have 92 and 576 \texttt{members}respectively, which will be useful to study the UV properties of stars in theextended turn-off and in various evolutionary stages from main-sequence to redclump. Future studies will carry out panchromatic and spectroscopic analysis ofnoteworthy members detected in this study.

UOCS. III. UVIT catalogue of open clusters with machine learning based membership using \textit{Gaia} EDR3 astrometry