Identification of Outer Galaxy Cluster Members Using Gaia DR3 and Multidimensional Simulation

The outer Galaxy presents a distinctive environment for investigating star formation. This study develops a novel approach to identify true cluster members based on unsupervised clustering using astrometry with significant uncertainties. As a proof of concept, we analyze three outer Galactic young s...

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Veröffentlicht in:The Astronomical journal Jg. 170; H. 3; S. 172 - 191
Hauptverfasser: Patel, Vishwas, Hora, Joseph L., Ashby, Matthew L. N., Vig, Sarita
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Madison The American Astronomical Society 01.09.2025
IOP Publishing
Schlagworte:
Algorithms
Astrometry
Cluster analysis
Clustering
Computational astronomy
Computer simulation
Dimensional analysis
Estimates
Galaxies
Infrared astronomy
Kinematics
Monte Carlo simulation
Star & galaxy formation
Star formation
Star forming regions
Stars
Uncertainty
Young star clusters
Young stellar objects
ISSN:0004-6256, 1538-3881
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Zusammenfassung:The outer Galaxy presents a distinctive environment for investigating star formation. This study develops a novel approach to identify true cluster members based on unsupervised clustering using astrometry with significant uncertainties. As a proof of concept, we analyze three outer Galactic young stellar object (YSO) clusters at different distances and densities within 65 ∘  <  l  < 265 ∘ , each known to contain >100 members based on the Star Formation in Outer Galaxy (SFOG; E. Winston et al. 2020) catalog. The 618 YSO clusters in the SFOG data set were based on 2D clustering. In this contribution, we apply the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN * ) algorithm to the precise Gaia DR3 astrometry to assign YSO cluster membership. A Monte Carlo simulation coupled with the HDBSCAN * (HDBSCAN-MC algorithm) addresses YSO astrometric uncertainties through 5D clustering. We introduce the Generation Of cLuster anD FIeld STar (GOLDFIST) simulation to enable robust membership determination, performing an unsupervised clustering analysis in higher-dimensional feature space while accommodating measurement errors. In this study, we extended our approach to distant outer galaxy YSOs and clusters with larger astrometric uncertainties. The results include the discovery of new members in the previously identified clusters. We also analyze the known stars in the clusters and confirm their membership. The derived membership probabilities are included in the provided cluster catalogs. The more accurately predicted simulation distance estimates closely agree, within uncertainty limits, with the median distance estimates derived from Gaia data, and are compared with the kinematic distances from the Wide-field Infrared Survey Explorer H ii survey.
Bibliographie:AAS63819
Interstellar Matter and the Local Universe
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ISSN:0004-6256
1538-3881
DOI:10.3847/1538-3881/adf187