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相关论文: Membership determination in open clusters using th…

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$Context$. Gaia Second Data Release provides precise astrometry and photometry for more than 1.3 billion sources. This catalog opens a new era concerning the characterization of open clusters and test stellar models, paving the way for a…

Clustering analysis, a classical issue in data mining, is widely used in various research areas. This article aims at proposing a self-adaption grey DBSCAN clustering (SAG-DBSCAN) algorithm. First, the grey relational matrix is used to…

机器学习 · 计算机科学 2019-12-30 Shizhan Lu

We systematically searched for open clusters in the solar neighborhood within 500 pc using pyUPMASK and HDBSCAN clustering algorithms based on {\it Gaia} DR3. Taking into consideration that the physical size for most open clusters is less…

太阳与恒星天体物理 · 物理学 2023-03-01 Songmei Qin , Jing Zhong , Tong Tang , Li Chen

Density-based clustering techniques are used in a wide range of data mining applications. One of their most attractive features con- sists in not making use of prior knowledge of the number of clusters that a dataset contains along with…

机器学习 · 计算机科学 2018-07-24 Roberto Pirrone , Vincenzo Cannella , Sergio Monteleone , Gabriella Giordano

In this work we present a method to identify possible members of globular clusters using data from Gaia DR2. The method consists of two stages: the first one based on a clustering algorithm, and the second one based on the analysis of the…

天体物理仪器与方法 · 物理学 2019-08-07 I. H. Bustos Fierro , J. H. Calderón

The open clusters fundamental physical parameters are important tools to understand the formation and evolution of the Galactic disk and as grounding tests for star formation and evolution models. However only a small fraction of the known…

星系天体物理 · 物理学 2010-05-24 Wagner J. B. Corradi , Francisco F. S. Maia , Joao F. C. Santos

A detailed study of stellar populations in Milky Way (MW) satellite galaxies remains an observational challenge due to their faintness and fewer spectroscopically confirmed member stars. We use unsupervised machine learning methods to…

天体物理仪器与方法 · 物理学 2023-11-27 Devika K Divakar , Pallavi Saraf , Sivarani Thirupathi , Vijayakumar H Doddamani

Despite having data for over 10^9 stars from Gaia, only less than 10^4 star clusters and candidates have been discovered. Particularly, distant star clusters are rarely identified, due to the challenges posed by heavy extinction and great…

星系天体物理 · 物理学 2023-08-09 Zhihong He , Yangping Luo , Kun Wang , Anbing Ren , Liming Peng , Qian Cui , Xiaochen Liu , Qingquan Jiang

Interstellar polarimetric data of the six open clusters Hogg 15, NGC 6611, NGC 5606, NGC 6231, NGC 5749 and NGC 6250 have been used to estimate the membership probability for the stars within them. For proper-motion member stars, the…

星系天体物理 · 物理学 2015-06-12 Biman J. Medhi , Motohide Tamura

Open clusters are groups of stars that form at the same time, making them an ideal laboratory to test theories of star formation, stellar evolution, and dynamics in the Milky Way disk. However, the utility of an open cluster can be limited…

星系天体物理 · 物理学 2022-01-12 Karl Jaehnig , Jonathan Bird , Kelly Holley-Bockelmann

The unprecedented precision of Gaia has led to a paradigm shift in membership determination of open clusters where a variety of machine learning (ML) models can be employed. In this paper, we apply the unsupervised Gaussian Mixture Model…

星系天体物理 · 物理学 2024-01-22 Md Mahmudunnobe , Priya Hasan , Mudasir Raja , Md Saifuddin , S N Hasan

Density-based clustering has found numerous applications across various domains. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is capable of finding clusters of varied shapes that are not linearly…

数据库 · 计算机科学 2019-12-03 Vinayak Mathur , Jinesh Mehta , Sanjay Singh

The Density Based Spatial Clustering of Applications with Noise (DBSCAN) is a topometric algorithm used to cluster spatial data that are affected by background noise. For the first time, we propose the use of this method for the detection…

天体物理仪器与方法 · 物理学 2015-06-11 A. Tramacere , C. Vecchio

We introduce a new method to determine galaxy cluster membership based solely on photometric properties. We adopt a machine learning approach to recover a cluster membership probability from galaxy photometric parameters and finally derive…

宇宙学与河外天体物理 · 物理学 2020-02-26 P. A. A. Lopes , A. L. B. Ribeiro

Recent advancements in neutron and X-ray sources, instrumentation and data collection modes have significantly increased the experimental data size (which could easily contain 10$^{8}$ -- 10$^{10}$ data points), so that conventional…

计算机视觉与模式识别 · 计算机科学 2018-09-25 Yawei Hui , Yaohua Liu

The Gaia Data Release 2 (DR2) provided an unprecedented volume of precise astrometric and excellent photometric data. In terms of data mining the Gaia catalogue, machine learning methods have shown to be a powerful tool, for instance in the…

星系天体物理 · 物理学 2019-07-03 A. Castro-Ginard , C. Jordi , X. Luri , T. Cantat-Gaudin , L. Balaguer-Núñez

We report 541 new open cluster candidates in Gaia EDR3 through revisiting the cluster results from an earlier analysis of the Gaia DR2, which revealed nearly a thousand open cluster candidates in the solar neighborhood (mostly d < 3 kpc)…

星系天体物理 · 物理学 2022-05-18 Zhihong He , Chunyan Li , Jing Zhong , Guimei Liu , Leya Bai , Songmei Qin , Yueyue Jiang , Xi Zhang , Li Chen

Context. Near open clusters as Pleiades, Praesepe and Blanco 1 have been extensively studied due to their proximity to the Sun. The Gaia data brings the opportunity to investigate these clusters, since it contains valuable astrometric and…

星系天体物理 · 物理学 2023-09-27 Jeison Alfonso , Alejandro García-Varela

The next generation of data-intensive surveys are bound to produce a vast amount of data, which can be dealt with using machine-learning methods to explore possible correlations within the multi-dimensional parameter space. We explore the…

Open clusters are among the most useful and widespread tracers of Galactic structure. The completeness of the Galactic open cluster census, however, remains poorly understood. For the first time ever, we establish the selection function of…