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arXiv 0712.1297astro-ph
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用三维Voronoi镶嵌法揭示局部超星系团的结构

The Structure of the Local Supercluster of Galaxies Revealed by the Three-Dimensional Voronoi's Tessellation Method

O. V. Melnyk, A. A. Elyiv, I. B. Vavilova

摘要:

3D Voronoi的镶嵌方法首先被应用于识别超星系团结构中的星系群。正在考虑的样本由超过7000个星系的本地超星系团(LS)的径向速度高达3100公里/秒。由于LS星表本质上的非均匀性,有人建议以“人工”的方式放大距离,使星系的浓度随着距离的增加而变化,这是一个具有与完全均匀星表相同的指数β的幂函数。各种参数的集群考虑:α(0.01,0.1,1%)的一部分,星系,其中有一个Voronoi的细胞的相对体积小于随机分布的临界值; β = 0,这符合随机星系分布; β = 0.7,这是接近煎饼星系分布。结果表明,Voronoi的镶嵌方法对β参数的依赖性较弱,且随着α参数的增加,富结构星系的数量逐渐增加,而贫结构星系的数量逐渐减少。通过与Karachentsev动力学方法得到的群的比较表明,所有分量一致的群的数目为22%。作为一个整体,动力学的方法更适合于识别人口稀少的星系群,而3D Voronoi的镶嵌方法更适合于人口稠密的星系群。

英文摘要:

3D Voronoi's tessellation method was first applied to identify groups of galaxies in the structure of a supercluster. The sample under consideration consists of more than 7000 galaxies of the Local Supercluster (LS) with radial velocities up to 3100 km/s. Because of an essential non-homogeneity of the LS catalogue, it was proposed to overscale distances in such an ''artificial'' way that the concentration of galaxies was varying as with increase of the distance a power-behaved function with the same exponent beta as for the full homogeneous catalogue. Various parameters of clustering were taking into account: alpha (0.01, 0.1, 1%) as the part of galaxies, which have the relative volume of a Voronoi's cell smaller than the critical one for the random distribution; beta = 0, which fits to the random galaxy distribution; beta = 0.7, which is close to the pancake galaxy distribution. It is revealed that Voronoi's tessellation method depends weakly on beta-parameter, and the number of galaxies in rich structures is growing rather than in poor ones with increase of alpha-parameter. The comparison of the groups derived with the groups obtained by Karachentsev's dynamical method shows that the number of groups, which coincides by all the components, is 22%. As a whole, the dynamical method is more preferred for identifying sparsely populated galaxy groups, whereas 3D Voronoi's tessellation method is preferred for more populated ones.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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