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We propose a new hierarchical method which uses dynamical arguments to find and describe substructures in galaxy clusters. This method (hereafter h--method or h--analysis) uses a hierarchical clustering analysis to determine the…

天体物理学 · 物理学 2007-05-23 Arturo Serna , Daniel Gerbal

In order to study the stellar population and possible substructures in the outskirts of Double Cluster $h$ and $\chi$ Persei, we investigate using the GAIA DR2 data a sky area of about 7.5 degrees in radius around the Double Cluster cores.…

星系天体物理 · 物理学 2019-04-03 Jing Zhong , Li Chen , M. B. N. Kouwenhoven , Lu Li , Zhengyi Shao , Jinliang Hou

We develop the Blooming Tree Algorithm, a new technique that uses spectroscopic redshift data alone to identify the substructures and the surrounding groups of galaxy clusters, along with their member galaxies. Based on the estimated…

星系天体物理 · 物理学 2018-06-21 Heng Yu , Antonaldo Diaferio , Ana Laura Serra , Marco Baldi

The structure of open clusters provides key insights into their evolution and the dynamics of the Milky Way. Using Gaia DR3 data, we applied a hierarchical clustering algorithm to the open cluster NGC 752 based on the kinematical…

星系天体物理 · 物理学 2026-02-10 Delong Jia , Heng Yu , Zhengyi Shao , Lu Li

The publication of the Gaia Data Release 2 (Gaia DR2) opens a new era in Astronomy. It includes precise astrometric data (positions, proper motions and parallaxes) for more than $1.3$ billion sources, mostly stars. To analyse such a vast…

星系天体物理 · 物理学 2018-10-17 A. Castro-Ginard , C. Jordi , X. Luri , F. Julbe , M. Morvan , L. Balaguer-Núñez , T. Cantat-Gaudin

Hierarchical clustering is a common algorithm in data analysis. It is unique among many clustering algorithms in that it draws dendrograms based on the distance of data under a certain metric, and group them. It is widely used in all areas…

天体物理仪器与方法 · 物理学 2022-11-14 Heng Yu , Xiaolan Hou

The description of complex configuration is a difficult issue. We present a powerful technique for cluster identification and characterization. The scheme is designed to treat with and analyze the experimental and/or simulation data from…

统计力学 · 物理学 2013-08-29 Guangcai Zhang , Aiguo Xu , Guo Lu , Zeyao Mo

We present a new geometrical method aimed at determining the members of open clusters. The methodology estimates, in an N-dimensional space, the membership probabilities by means of the distances between every star and the cluster central…

太阳与恒星天体物理 · 物理学 2016-02-10 Laura Sampedro , Emilio J. Alfaro

We applied the newly developed rose diagram overlay method to detect the layered structure of 88 nearby open clusters ($\leq$500~pc) on the three projections after the distance correction of their member stars, based on the catalog in…

星系天体物理 · 物理学 2023-05-18 Qingshun Hu , Yu Zhang , Ali Esamdin , Hong Wang , Mingfeng Qin

In this work, we analysed young stellar clusters with spatial and kinematic coherence in the Orion star-forming complex. For this study, we selected a sample of pre-main sequence candidates using parallaxes, proper motions and positions on…

Based on the most complete sample of Galactic open star clusters up to 1.8 kpc, we performed statistical analysis of the distribution of open cluster parameters in order to understand the Galactic structure. The geometrical characteristics…

星系天体物理 · 物理学 2017-07-31 Yogesh C. Joshi

The physical nature of a series of 20 new open clusters is confirmed employing existing data on putative star members, mainly from second Gaia Data Release (DR2). The clusters were discovered as overdensities of stars by visual inspection…

太阳与恒星天体物理 · 物理学 2021-06-23 Juan Casado

Star clusters are often hard to find, as they may lie in a dense field of background objects or, because in the case of embedded clusters, they are surrounded by a more dispersed population of young stars. This paper discusses four…

星系天体物理 · 物理学 2011-02-16 S. Schmeja

A new approach to the study of the large-scale stellar cluster distribution in the Galaxy based on two-point correlation techniques is presented. The basic formalism for this method is outlined and its applications are then investigated by…

天体物理学 · 物理学 2009-10-30 M. Lopez-Corredoira , F. Garzon , P. L. Hammersley , T. J. Mahoney

This paper introduces a new method to search for unresolved binary stars in open star clusters. The work aims at improving the approach introduced previously, which employs the (H-W2)-W1 versus W2-(BP-K) photometric diagram. This diagram,…

星系天体物理 · 物理学 2026-04-23 Varvara O. Mikhnevich , Anastasiia Plotnikova , Giovanni Carraro , Anton F. Seleznev

Context. Understanding the formation and evolution of star clusters in the Milky Way requires precise identification of clusters that form binary or multiple systems. Such systems offer valuable insight into the dynamical processes and…

星系天体物理 · 物理学 2025-01-22 Tali Palma , Valeria Coenda , Gustavo Baume , Carlos Feinstein

Context: Convergent point (CP) search methods are important tools for studying the kinematic properties of open clusters and young associations whose members share the same spatial motion. Aims: We present a new CP search strategy based on…

天体物理仪器与方法 · 物理学 2011-12-16 P. A. B. Galli , R. Teixeira , C. Ducourant , C. Bertout , P. Benevides-Soares

Current catalogues of open clusters are rather heterogeneous and incomplete lists of clusters than true catalogues. Before there has been no attempts of automatic search for open clusters in huge photometric catalogues using homogeneous…

天体物理学 · 物理学 2007-05-23 Ivan Zolotukhin , Sergey Koposov , Elena Glushkova

We present the first detailed observational picture of a possible ongoing massive cluster hierarchical assembly in the Galactic disk as revealed by the analysis of the stellar full phase-space (3D positions and kinematics and…

The immense amount of time series data produced by astronomical surveys has called for the use of machine learning algorithms to discover and classify several million celestial sources. In the case of variable stars, supervised learning…

太阳与恒星天体物理 · 物理学 2022-10-12 R. Pantoja , M. Catelan , K. Pichara , P. Protopapas
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