Matching Globular Cluster Models to Observations
Matching Globular Cluster Models to Observations
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DOI：
10.3847/1538-4357/abed49
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发表时间：
2021-03
期刊：
影响因子：
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通讯作者：
N. Z. Rui;K. Kremer;Newlin C. Weatherford;S. Chatterjee;F. Rasio;C. Rodriguez;Claire S. Ye
中科院分区：
文献类型：
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作者：
N. Z. Rui;K. Kremer;Newlin C. Weatherford;S. Chatterjee;F. Rasio;C. Rodriguez;Claire S. Ye
作为古老的、受引力束缚的恒星群，球状星团代表着丰富的、充满活力的实验室，其特征是高频率的动态相互作用，加上复杂的恒星演化。利用文献中的表面亮度和速度弥散曲线，我们将59个银河系球状星团与CMC星团目录中的动力学模型拟合。没有进行任何插值，也没有任何直接的努力来拟合任何特定的星团，26个球状星团至少与我们的一个模型很好地匹配。我们特别讨论了核心坍缩星团NGC 6293、NGC 6397、NGC 6681和NGC 6624，以及非核心坍缩星团NGC 288、NGC 4372和NGC 5897。由于NGC 6624在主CMC星团目录上缺乏很好的拟合快照，我们运行了六个额外的模型来改进拟合。我们计算了质量分离的度量，探索了紧凑天体源的产生，如毫秒脉冲星、灾难性变量、低质量x射线双星和恒星质量黑洞，找到了与观测结果合理一致的地方。此外，我们密切模仿观测切割，从我们的模型中提取二进制分数，发现很好的一致性，除了在核心坍缩星团的密集核心区域。本文附带了一些python方法，用于检查可公开访问的CMC Cluster Catalog，以及使用CMC生成的任何其他模型。
As ancient, gravitationally bound stellar populations, globular clusters represent abundant, vibrant laboratories, characterized by high frequencies of dynamical interactions, coupled to complex stellar evolution. Using surface brightness and velocity dispersion profiles from the literature, we fit 59 Milky Way globular clusters to dynamical models from the CMC Cluster Catalog. Without performing any interpolation, and without any directed effort to fit any particular cluster, 26 globular clusters are well matched by at least one of our models. We discuss in particular the core-collapsed clusters NGC 6293, NGC 6397, NGC 6681, and NGC 6624, and the non-core-collapsed clusters NGC 288, NGC 4372, and NGC 5897. As NGC 6624 lacks well-fitting snapshots on the main CMC Cluster Catalog, we run six additional models in order to refine the fit. We calculate metrics for mass segregation, explore the production of compact object sources such as millisecond pulsars, cataclysmic variables, low-mass X-ray binaries, and stellar-mass black holes, finding reasonable agreement with observations. In addition, closely mimicking observational cuts, we extract the binary fraction from our models, finding good agreement, except in the dense core regions of core-collapsed clusters. Accompanying this paper are a number of python methods for examining the publicly accessible CMC Cluster Catalog, as well as any other models generated using CMC.