High-precision proper motions and radial velocities of 1046 stars are used to determine member stars using three-dimensional （3D） kinematics for open clus- ter NGC 188 based on the density-based spatial clustering o...High-precision proper motions and radial velocities of 1046 stars are used to determine member stars using three-dimensional （3D） kinematics for open clus- ter NGC 188 based on the density-based spatial clustering of applications with noise （DBSCAN） clustering algorithm. By implementing this algorithm, 472 member stars in the cluster are obtained with 3D kinematics. The color-magnitude diagram （CMD） of the 472 member stars using 3D kinematics shows a well-defined main sequence and a red giant branch, which indicate that the DBSCAN clustering algorithm is very effective for membership determination. The DBSCAN clustering algorithm can ef- fectively select probable member stars in 3D kinematic space without any assumption about the distribution of the cluster or field stars. Analysis results show that the CMD of member stars is significantly clearer than the one based on 2D kinematics, which al- lows us to better constrain the cluster members and estimate their physical parameters. Using the 472 member stars, the average absolute proper motion and radial velocity are determined to be （PMα, PMδ） = （-2.58 ± 0.22, ＋0.17 ± 0.18） mas yr-1 and Vr = -42.35 ± 0.05 km s-1, respectively. Our values are in good agreement with values derived by other authors.展开更多
利用疏散星团NGC 188所在天区的1046颗恒星样本的高精度3维(3D)运动学数据(自行和视向速度)测试了DBSCAN(Density-Based Spatial Clustering of Applications with Noise)聚类算法的成员判定效果.为了避免自行和视向速度的单位不一致带...利用疏散星团NGC 188所在天区的1046颗恒星样本的高精度3维(3D)运动学数据(自行和视向速度)测试了DBSCAN(Density-Based Spatial Clustering of Applications with Noise)聚类算法的成员判定效果.为了避免自行和视向速度的单位不一致带来的影响,在数据预处理阶段将3个分量的数据统一标准化至[0,1]区间.利用第k个最近邻点距离方法分析了1046颗恒星样本在标准化无量纲3D速度空间的分布特征,再根据第k个最近邻点距离随k值的变化趋势确定了DBSCAN聚类算法的输入参数(Eps,MinPts),最后利用DBSCAN聚类算法分离出497颗3D运动学成员星.分析结果表明得到的3D运动学成员星是可靠的.展开更多
基金supported by the School Foundation of Changzhou University(Grant No.ZMF1002121)
文摘High-precision proper motions and radial velocities of 1046 stars are used to determine member stars using three-dimensional （3D） kinematics for open clus- ter NGC 188 based on the density-based spatial clustering of applications with noise （DBSCAN） clustering algorithm. By implementing this algorithm, 472 member stars in the cluster are obtained with 3D kinematics. The color-magnitude diagram （CMD） of the 472 member stars using 3D kinematics shows a well-defined main sequence and a red giant branch, which indicate that the DBSCAN clustering algorithm is very effective for membership determination. The DBSCAN clustering algorithm can ef- fectively select probable member stars in 3D kinematic space without any assumption about the distribution of the cluster or field stars. Analysis results show that the CMD of member stars is significantly clearer than the one based on 2D kinematics, which al- lows us to better constrain the cluster members and estimate their physical parameters. Using the 472 member stars, the average absolute proper motion and radial velocity are determined to be （PMα, PMδ） = （-2.58 ± 0.22, ＋0.17 ± 0.18） mas yr-1 and Vr = -42.35 ± 0.05 km s-1, respectively. Our values are in good agreement with values derived by other authors.
文摘利用疏散星团NGC 188所在天区的1046颗恒星样本的高精度3维(3D)运动学数据(自行和视向速度)测试了DBSCAN(Density-Based Spatial Clustering of Applications with Noise)聚类算法的成员判定效果.为了避免自行和视向速度的单位不一致带来的影响,在数据预处理阶段将3个分量的数据统一标准化至[0,1]区间.利用第k个最近邻点距离方法分析了1046颗恒星样本在标准化无量纲3D速度空间的分布特征,再根据第k个最近邻点距离随k值的变化趋势确定了DBSCAN聚类算法的输入参数(Eps,MinPts),最后利用DBSCAN聚类算法分离出497颗3D运动学成员星.分析结果表明得到的3D运动学成员星是可靠的.
