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arXiv 1002.4401astro-ph.GA
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等级形成星团的性质

Properties of hierarchically forming star clusters

Th. Maschberger, C. J. Clarke, I. A. Bonnell, P. Kroupa

摘要:

我们进行了系统的分析早期(< 0.5万年)的集群和恒星初始质量函数的湍流碎裂模拟的演变。这些大规模的模拟第一次提供了一个机会,IMF的变化和恒星属性和集群丰富度之间的相关性的统计分析。典型的演化场景涉及小n星团中的恒星形成,然后逐渐合并;第一批形成的恒星是大质量恒星的种子,并在质量获取方面取得领先地位。这些巨大的种子最终会进入星团的核心,而大部分质量较低的新星会在星团的外部形成。由此产生的集群,因此大规模隔离的年龄为0.5万年,虽然大规模隔离的签名是在合并过程中减弱。我们发现,由此产生的IMF有一个较小的指数(α =1.8-2.2)比Salpeter值(α =2.35)。子星团中的IMF在质量仅略大于最大质量恒星时被截断(这取决于星团的丰富度),并且排除了150 Msun的普遍质量上限。我们还发现,模拟显示的IGIMF效应的迹象,提出的Weideland和Kroupa,大质量恒星的频率被抑制在综合IMF相比,IMF在个别集群。我们确定集群通过使用最小生成树算法,可以很容易地比较观测调查数据和湍流破碎模型的预测。特别是,我们提出了定量预测的性质,如集群形态,质量分离的程度,上斜坡的IMF和集群丰富度和最大恒星质量之间的关系。[删节]

英文摘要:

We undertake a systematic analysis of the early (< 0.5 Myr) evolution of clustering and the stellar initial mass function in turbulent fragmentation simulations. These large scale simulations for the first time offer the opportunity for a statistical analysis of IMF variations and correlations between stellar properties and cluster richness. The typical evolutionary scenario involves star formation in small-n clusters which then progressively merge; the first stars to form are seeds of massive stars and achieve a headstart in mass acquisition. These massive seeds end up in the cores of clusters and a large fraction of new stars of lower mass is formed in the outer parts of the clusters. The resulting clusters are therefore mass segregated at an age of 0.5 Myr, although the signature of mass segregation is weakened during mergers. We find that the resulting IMF has a smaller exponent (alpha=1.8-2.2) than the Salpeter value (alpha=2.35). The IMFs in subclusters are truncated at masses only somewhat larger than the most massive stars (which depends on the richness of the cluster) and an universal upper mass limit of 150 Msun is ruled out. We also find that the simulations show signs of the IGIMF effect proposed by Weidner & Kroupa, where the frequency of massive stars is suppressed in the integrated IMF compared to the IMF in individual clusters. We identify clusters through the use of a minimum spanning tree algorithm which allows easy comparison between observational survey data and the predictions of turbulent fragmentation models. In particular we present quantitative predictions regarding properties such as cluster morphology, degree of mass segregation, upper slope of the IMF and the relation between cluster richness and maximum stellar mass. [abridged]

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