论文标题
观察性偏见和年轻的大量聚类表征I. 2D透视效应
Observational Bias and Young Massive Cluster Characterisation I. 2D Perspective Effects
论文作者
论文摘要
了解高质量星团的形成和演变需要进行理论和观察数据之间的比较。不幸的是,尽管可以使用模拟区域的整个相空间,但通常只有部分2D空间和运动学数据可用于观察到的区域。这就提出了一个问题,即是否仅从2D数据确定的群集参数是可靠的,并且代表了群集实际参数以及视线方向的影响。在本文中,我们得出了由与完整6D相位空间相撞形成的模拟群集的参数,并将它们与群集的三个不同2D视线方向衍生的参数进行比较。当观看2D与3D的群集时,我们可以得出相同的定性结论,但是在2D中观看时,该得出的定量结论可能是不准确的。最大的差异发生在群集的感知运动学中,在某些方向上,当群集实际上在收缩时似乎正在扩大。群集密度化合物的增加是现有的透视问题,从而降低了来自不同方向的属性的相对准确性和一致性。这对于确定集群中存在的子集群的数字和成员资格尤其有问题。我们发现随着群集的发展,在2D中正确识别的子集群的分数减小,在我们的群集的进化终点下达到3.4%。
Understanding the formation and evolution of high mass star clusters requires comparisons between theoretical and observational data to be made. Unfortunately, while the full phase space of simulated regions is available, often only partial 2D spatial and kinematic data is available for observed regions. This raises the question as to whether cluster parameters determined from 2D data alone are reliable and representative of clusters real parameters and the impact of line-of-sight orientation. In this paper we derive parameters for a simulated cluster formed from a cloud-cloud collision with the full 6D phase space, and compare them with those derived from three different 2D line-of-sight orientations for the cluster. We show the same qualitative conclusions can be reached when viewing clusters in 2D versus 3D, but that drawing quantitative conclusions when viewing in 2D is likely to be inaccurate. The greatest divergence occurs in the perceived kinematics of the cluster, which in some orientations appears to be expanding when the cluster is actually contracting. Increases in the cluster density compounds pre-existing perspective issues, reducing the relative accuracy and consistency of properties derived from different orientations. This is particularly problematic for determination of the number, and membership, of subclusters present in the cluster. We find the fraction of subclusters correctly identified in 2D decreases as the cluster evolves, reaching less than 3.4% at the evolutionary end point for our cluster.