| dc.description.abstract |
Agarwal et al. (2021MNRAS.502.2582A) using Gaia DR2 (2018A&A...616A...1G, Cat. I/345) data with their novel machine learning membership determination algorithm found hints of tidal tails in NGC 752. Also, Hu et al. (2021ApJ...912....5H, Cat. J/ApJ/912/5) also identify the elongated morphology of the peripheral regions of NGC 752 from the Gaia DR2 data using the members identified by Cantat-Gaudin et al. (2018A&A...618A..93C, Cat. J/A+A/618/A93).
As the first step, we do a membership selection in NGC 752 from the Gaia EDR3 (2021A&A...649A...1G, Cat. I/350) data set is carried out in a region of radius 5 degrees around its centre. This sample is termed All sources. We use ML-MOC (Agarwal et al. 2021MNRAS.502.2582A) to identify cluster members using the proper motion and parallax information. It identifies cluster members in the PM-ω parameter space, independent of the spatial density of the cluster, thereby allowing for the identification of faint extended spatial structures such as tidal tails |
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