J/A+A/675/A68 ML tool for open cluster membership (van Groeningen+, 2023)
A machine learning-based tool for open cluster membership determination
in Gaia DR3.
van Groeningen M.G.J., Castro-Ginard A., Brown A.G.A., Casamiquela L.,
Jordi C.
<Astron. Astrophys. 675, A68 (2023)>
=2023A&A...675A..68V 2023A&A...675A..68V (SIMBAD/NED BibCode)
ADC_Keywords: Milky Way ; Clusters, open ; Optical
Keywords: methods: data analysis - open clusters and associations: general -
catalogs
Abstract:
Membership studies characterising open clusters with Gaia data, most
using DR2, are so far limited at magnitude G=18 due to astrometric
uncertainties at the faint end. Our goal is to extend current open
cluster membership lists with faint members and to characterise the
low-mass end, which members are important for many applications, in
particular for ground-based spectroscopic surveys. We use a deep
neural network architecture to learn the distribution of highly
reliable open cluster member stars around known clusters. After that,
we use the trained network to estimate new open cluster members based
on their similarities in a high dimensional space, five-dimensional
astrometry plus the three photometric bands. Due to the improved
astrometric precisions of Gaia DR3 with respect to DR2, we are able
to homogeneously detect new faint member stars (G>18) for the known
open cluster population. Our methodology can provide extended membership
lists for open clusters down to the limiting magnitude of Gaia, which
will enable further studies to characterise the open cluster population,
e.g. estimation of their masses, or their dynamics. These extended
membership lists are also ideal target lists for forthcoming
ground-based spectroscopic surveys.
Description:
In this paper we present a machine-learning based method for determining
members of open clusters. We have applied the method to derive the members
for 2492 open clusters.
This file contains the members for 2492 clusters with a membership
probability of at least 5 percent. All columns come from Gaia DR3, except
for the membership probability.
File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
clusters.dat 69 2492 List of open clusters
members.dat 199 4233007 Members of 2492 open clusters
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See also:
I/355 : Gaia DR3 Part 1. Main source (Gaia Collaboration, 2022)
Byte-by-byte Description of file: clusters.dat
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Bytes Format Units Label Explanations
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1- 17 A17 --- Cluster Cluster name
19- 20 I2 h RAh Right ascension (J2000)
22- 23 I2 min RAm Right ascension (J2000)
25- 29 F5.2 s RAs Right ascension (J2000)
32 A1 --- DE- Declination sign (J2000)
33- 34 I2 deg DEd Declination (J2000)
36- 37 I2 arcmin DEm Declination (J2000)
39- 42 F4.1 arcsec DEs Declination (J2000)
46- 69 A24 --- SName Simbad name
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Byte-by-byte Description of file: members.dat
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Bytes Format Units Label Explanations
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1- 19 I19 --- GaiaDR3 Gaia DR3 source ID (source_id)
21- 44 F24.20 deg RAdeg Right Ascension (ICRS) (ra)
46- 69 E24.15 deg DEdeg Declination (ICRS) (dec)
70- 93 E24.16 mas Plx Absolute stellar parallax (parallax)
95-118 E24.16 mas/yr pmRA Proper motion in right ascension direction
(pmra)
120-143 E24.16 mas/yr pmDE Proper motion in declination direction (pmdec)
145-154 F10.7 mag Gmag G-band mean magnitude (photgmean_mag)
156-165 F10.7 mag BPmag BP-band mean magnitude (photbpmean_mag)
167-176 F10.7 mag RPmag RP-band mean magnitude (photrpmean_mag)
178-194 A17 --- Cluster Cluster name (cluster)
196-199 F4.2 --- Pmemb Membership probability (PMemb)
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Acknowledgements:
Matthijs van Groeningen, matthijsvangroeningen(at)gmail.com
(End) Patricia Vannier [CDS] 19-May-2023