As groups of coeval stars born from the same molecular cloud,an open cluster(OC)is an ideal laboratory for studying the structure and dynamical evolution of the Milky Way.The release of high-precision Gaia Early Data ...As groups of coeval stars born from the same molecular cloud,an open cluster(OC)is an ideal laboratory for studying the structure and dynamical evolution of the Milky Way.The release of high-precision Gaia Early Data Release 3(Gaia EDR3)and modern machine-learning methods offer unprecedented opportunities to identify OCs.In this study,we extended conventional HDBSCAN(e-HDBSCAN)for searching for new OCs in Gaia EDR3.A pipeline was developed based on the parallel computing technique to blindly search for OCs from Gaia EDR3within Galactic latitudes∣b∣<25°.As a result,we obtained 3787 star clusters,of which 83 new OCs were reported after cross-match and visual inspection.At the same time,the main star cluster parameters are estimated by color-magnitude diagram fitting.The study significantly increases the sample size and physical parameters of OCs in the catalog of OCs.It shows the incompleteness of the census of OCs across our Galaxy.展开更多
Open clusters(OCs)serve as invaluable tracers for investigating the properties and evolution of stars and galaxies.Despite recent advancements in machine learning clustering algorithms,accurately discerning such clust...Open clusters(OCs)serve as invaluable tracers for investigating the properties and evolution of stars and galaxies.Despite recent advancements in machine learning clustering algorithms,accurately discerning such clusters remains challenging.We re-visited the 3013 samples generated with a hybrid clustering algorithm of FoF and pyUPMASK.A multi-view clustering(MvC)ensemble method was applied,which analyzes each member star of the OC from three perspectives—proper motion,spatial position,and composite views—before integrating the clustering outcomes to deduce more reliable cluster memberships.Based on the MvC results,we further excluded cluster candidates with fewer than ten member stars and obtained 1256 OC candidates.After isochrone fitting and visual inspection,we identified 506 candidate OCs in the Milky Way.In addition to the 493 previously reported candidates,we finally discovered 13 high-confidence new candidate clusters.展开更多
基金supported by the National SKA Program of China No.2020SKA0110300Joint Research Fund in Astronomy(U1831204)under cooperative agreement between the National Natural Science Foundation of China(NSFC)+5 种基金the Chinese Academy of Sciences(CAS)the National Key Research and Development Program of China(2018YFA0404603)the NSFC(Nos.11863002 and 11961141001)supported by the Yunnan Academician Workstation of Wang Jingxiu(No.202005AF150025)China Manned Space Project with NO.CMS-CSST-2021-A08Sino-German Cooperation Project(No.GZ 1284)。
文摘As groups of coeval stars born from the same molecular cloud,an open cluster(OC)is an ideal laboratory for studying the structure and dynamical evolution of the Milky Way.The release of high-precision Gaia Early Data Release 3(Gaia EDR3)and modern machine-learning methods offer unprecedented opportunities to identify OCs.In this study,we extended conventional HDBSCAN(e-HDBSCAN)for searching for new OCs in Gaia EDR3.A pipeline was developed based on the parallel computing technique to blindly search for OCs from Gaia EDR3within Galactic latitudes∣b∣<25°.As a result,we obtained 3787 star clusters,of which 83 new OCs were reported after cross-match and visual inspection.At the same time,the main star cluster parameters are estimated by color-magnitude diagram fitting.The study significantly increases the sample size and physical parameters of OCs in the catalog of OCs.It shows the incompleteness of the census of OCs across our Galaxy.
基金supported by the National Key Research And Development Program of China(No.2022YFF0711500)the National Natural Science Foundation of China(NSFC,Grant No.12373097)+1 种基金the Basic and Applied Basic Research Foundation Project of Guangdong Province(No.2024A1515011503)the Guangzhou Science and Technology Funds(2023A03J0016)。
文摘Open clusters(OCs)serve as invaluable tracers for investigating the properties and evolution of stars and galaxies.Despite recent advancements in machine learning clustering algorithms,accurately discerning such clusters remains challenging.We re-visited the 3013 samples generated with a hybrid clustering algorithm of FoF and pyUPMASK.A multi-view clustering(MvC)ensemble method was applied,which analyzes each member star of the OC from three perspectives—proper motion,spatial position,and composite views—before integrating the clustering outcomes to deduce more reliable cluster memberships.Based on the MvC results,we further excluded cluster candidates with fewer than ten member stars and obtained 1256 OC candidates.After isochrone fitting and visual inspection,we identified 506 candidate OCs in the Milky Way.In addition to the 493 previously reported candidates,we finally discovered 13 high-confidence new candidate clusters.
