星团性质随机波动的贝叶斯方法
A Bayesian Approach Accounting for Stochastic Fluctuations in Stellar Cluster Properties
摘要：
星团的综合分光光度特性在星团与星团之间有很大的差异。它们以非平凡的方式分布在标准人口合成模型预测的平均属性周围。这是由于每个星团中有限（少量）发光恒星的随机质量分布，这些恒星可能是特别蓝色或特别红色。颜色分布很宽，通常远离高斯分布，特别是在年轻和中等年龄的星系团中，就像在相互作用的星系中发现的那样。当光度测量的集群被用来估计年龄和质量与标准模型，偏差是可以预期的。我们提出了一个贝叶斯方法，明确占随机性时，估计年龄和质量的星团，不能解决成恒星。基于蒙特卡罗模拟，我们开始探索的概率分布的星团性质得到了一组多波长光度数据。
英文摘要：
The integrated spectro-photometric properties of star clusters are subject to large cluster-to-cluster variations. They are distributed in non trivial ways around the average properties predicted by standard population synthesis models. This results from the stochastic mass distribution of the finite (small) number of luminous stars in each cluster, stars which may be either particularly blue or particularly red. The color distributions are broad and usually far from Gaussian, especially for young and intermediate age clusters, as found in interacting galaxies. When photometric measurements of clusters are used to estimate ages and masses in conjunction with standard models, biases are to be expected. We present a Bayesian approach that explicitly accounts for stochasticity when estimating ages and masses of star clusters that cannot be resolved into stars. Based on Monte-Carlo simulations, we are starting to explore the probability distributions of star cluster properties obtained given a set of multi-wavelength photometric data.
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