• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>PASJ: Publications of the Astronomical Society of Japan >Membership determination of open clusters based on a spectral clustering method
【24h】

Membership determination of open clusters based on a spectral clustering method

机译：基于光谱聚类方法的开放集群隶属厘定

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.
机译：我们提出了一种谱聚类（SC）方法，旨在在多维空间中分离开放集群的可靠成员。 SC方法是使用相似矩阵的特征向量执行群集划分的非参数聚类技术;不需要先前了解集群。与其他成员确定方法相比，该方法在处理多维数据时更灵活。我们使用这种方法将五个开放集群（哈迪斯，昏迷，Pleiades，PRAESEPE和NGC 188）分离的集群成员;获得了相当清洁的集群成员。我们发现SC方法可以从大量场恒星（重噪声）捕获少数集群成员（弱信号）。基于这些集群成员，我们计算卫星，昏迷，普利奥，群集的平均适当的动作和距离，我们的结果一般与其他作者的结果相一致。测试结果表明SC方法非常适合基于诸如GaIa数据的高精度多维天数数据来分离开簇的聚类成员。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号