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The spatial evolution of young massive clusters

机译:年轻块状星团的空间演化

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Context . There are a number of methods that identify stellar sub-structure in star forming regions, but these do not quantify the degree of association of individual stars – something which is required if we are to better understand the mechanisms and physical processes that dictate structure. Aims . We present the new novel statistical clustering tool “INDICATE” which assesses and quantifies the degree of spatial clustering of each object in a dataset, discuss its applications as a tracer of morphological stellar features in star forming regions, and to look for these features in the Carina Nebula (NGC 3372). Methods . We employ a nearest neighbour approach to quantitatively compare the spatial distribution in the local neighbourhood of an object with that expected in an evenly spaced uniform (i.e. definitively non-clustered) field. Each object is assigned a clustering index (“ I ”) value, which is a quantitative measure of its clustering tendency. We have calibrated our tool against random distributions to aid interpretation and identification of significant I values. Results . Using INDICATE we successfully recover known stellar structure of the Carina Nebula, including the young Trumpler 14-16, Treasure Chest and Bochum 11 clusters. Four sub-clusters contain no, or very few, stars with a degree of association above random which suggests these sub-clusters may be fluctuations in the field rather than real clusters. In addition we find: (1) Stars in the NW and SE regions have significantly different clustering tendencies, which is reflective of differences in the apparent star formation activity in these regions. Further study is required to ascertain the physical origin of the difference; (2) The different clustering properties between the NW and SE regions are also seen for OB stars and are even more pronounced; (3) There are no signatures of classical mass segregation present in the SE region – massive stars here are not spatially concentrated together above random; (4) Stellar concentrations are more frequent around massive stars than typical for the general population, particularly in the Tr14 cluster; (5) There is a relation between the concentration of OB stars and the concentration of (lower mass) stars around OB stars in the centrally concentrated Tr14 and Tr15, but no such relation exists in Tr16. We conclude this is due to the highly sub-structured nature of Tr16. Conclusions . INDICATE is a powerful new tool employing a novel approach to quantify the clustering tendencies of individual objects in a dataset within a user-defined parameter space. As such it can be used in a wide array of data analysis applications. In this paper we have discussed and demonstrated its application to trace morphological features of young massive clusters.
机译:语境。有很多方法可以识别恒星形成区域中的恒星亚结构,但是这些方法不能量化单个恒星的缔合程度,这是我们要更好地理解决定结构的机制和物理过程所必需的。目的。我们提出了一种新的新型统计聚类工具“ INDICATE”,该工具可以评估和量化数据集中每个对象的空间聚类程度,讨论其在恒星形成区域中作为形态恒星特征的示踪剂的应用,并在恒星形成区域中寻找这些特征。船状星云(NGC 3372)。方法 。我们采用最近邻方法来定量比较对象的局部邻域中的空间分布与在均匀间隔的均匀(即绝对非聚类)场中预期的空间分布。为每个对象分配一个聚类索引(“ I”)值,该值是对其聚类趋势的定量度量。我们已经针对随机分布对工具进行了校准,以帮助解释和识别重要的I值。结果。使用INDICATE,我们成功地恢复了Carina星云的已知星状结构,包括年轻的Trumpler 14-16,宝物箱和Bochum 11星团。四个子簇中没有或只有很少的恒星具有高于随机的关联度,这表明这些子簇可能是场中的波动,而不是真实的星团。此外,我们发现:(1)西北和东南区域的恒星具有明显不同的聚集趋势,这反映了这些区域的表观恒星形成活动的差异。需要进一步研究以确定差异的物理来源; (2)OB恒星在西北和东南区域之间的聚类性质也不同,而且更为明显。 (3)SE地区没有经典的质量偏析的标志-这里的大质量恒星在空间上不会集中在随机之上。 (4)大质量恒星周围的恒星集中度比普通人群高,特别是在Tr14星团中; (5)在中央集中的Tr14和Tr15中,OB恒星的浓度与OB恒星周围的(较低质量)恒星的浓度之间存在关系,但是Tr16中不存在这种关系。我们得出结论,这归因于Tr16的高度亚结构化性质。结论。 INDICATE是功能强大的新工具,它采用新颖的方法来量化用户定义的参数空间内数据集中各个对象的聚类趋势。因此,它可以用于各种数据分析应用程序中。在本文中,我们讨论并证明了其在跟踪年轻块状团簇的形态特征中的应用。

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