论文标题
M33中的年轻恒星簇的Gibbs点过程模型
Gibbs Point Process Model for Young Star Clusters in M33
论文作者
论文摘要
当应用于解决星系研究时，我们从空间统计文献中证明了吉布斯点过程模型的力量。我们对M33恒星形成络合物中物体的空间分布进行了严格的分析，包括巨型分子云（GMC）和年轻的恒星群集候选者（YSCCS）。我们根据它们之间的自然形成层次结构选择从GMC到YSCC的层次模型结构。这种方法通过自然考虑YSCCS分布中存在的不均匀性来规避经验两点相关函数分析的局限性。我们还研究了GMCS性质对其空间分布的影响。我们确认GMC和YSCC的分布高度相关。我们发现，与泊松过程相比，YSCC的空间分布在〜250 pc尺度上达到聚类模式的峰值。这种聚类主要发生在半腔距离> 〜4.5 kpc的区域中。此外，GMC及其质量的半乳酸距离对GMC和YSCC之间的相关强度具有强大的积极影响。我们概述了这些发现对我们对群集形成过程的理解的一些可能含义。
We demonstrate the power of Gibbs point process models from the spatial statistics literature when applied to studies of resolved galaxies. We conduct a rigorous analysis of the spatial distributions of objects in the star formation complexes of M33, including giant molecular clouds (GMCs) and young stellar cluster candidates (YSCCs). We choose a hierarchical model structure from GMCs to YSCCs based on the natural formation hierarchy between them. This approach circumvents the limitations of the empirical two-point correlation function analysis by naturally accounting for the inhomogeneity present in the distribution of YSCCs. We also investigate the effects of GMCs' properties on their spatial distributions. We confirm that the distribution of GMCs and YSCCs are highly correlated. We found that the spatial distributions of YSCCs reaches a peak of clustering pattern at ~250 pc scale compared to a Poisson process. This clustering mainly occurs in regions where the galactocentric distance >~4.5 kpc. Furthermore, the galactocentric distance of GMCs and their mass have strong positive effects on the correlation strength between GMCs and YSCCs. We outline some possible implications of these findings for our understanding of the cluster formation process.
