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arXiv 1209.2142astro-ph.GAastro-ph.CO
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用模型模拟器表征类Milky Way恒星晕的形成历史

Characterizing the formation history of Milky Way-like stellar haloes with model emulators

Facundo A. Gómez, Christopher E. Coleman-Smith, Brian W. O'Shea, Jason Tumlinson, Robert. L. Wolpert

摘要:

我们使用半解析模型ChemTreeN,再加上宇宙学的N体模拟,探索不同的星系形成的历史可以影响银河系类星系的恒星晕和他们的卫星人口的观测特性。高斯过程用于生成模型仿真器,其允许在p维输入参数空间的任何位置处统计地估计期望的模型输出集合。这使得人们能够比其他方式更快地探索整个输入参数空间的数量级。使用模拟观测数据集生成的ChemTreeN本身,我们表明,它是可以成功地恢复用于生成模拟观测值的输入参数向量,如果合并历史的主机晕是已知的。然而,我们的研究结果表明,对于一个给定的观测数据集的“最佳拟合”参数的确定是非常容易受到特定的合并历史的主机。非常不同的晕合并历史可以重现相同的观测数据集,如果“最佳拟合”参数允许从历史到历史的变化。因此,使用这些技术来描述银河系形成历史的尝试必须进行统计,分析高分辨率N体模拟的大样本。

英文摘要:

We use the semi-analytic model ChemTreeN, coupled to cosmological N-body simulations, to explore how different galaxy formation histories can affect observational properties of Milky Way-like galaxies' stellar haloes and their satellite populations. Gaussian processes are used to generate model emulators that allow one to statistically estimate a desired set of model outputs at any location of a p-dimensional input parameter space. This enables one to explore the full input parameter space orders of magnitude faster than could be done otherwise. Using mock observational data sets generated by ChemTreeN itself, we show that it is possible to successfully recover the input parameter vectors used to generate the mock observables if the merger history of the host halo is known. However, our results indicate that for a given observational data set the determination of "best fit" parameters is highly susceptible to the particular merger history of the host. Very different halo merger histories can reproduce the same observational dataset, if the "best fit" parameters are allowed to vary from history to history. Thus, attempts to characterize the formation history of the Milky Way using these kind of techniques must be performed statistically, analyzing large samples of high resolution N-body simulations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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