The parameter space of galaxy formation
The parameter space of galaxy formation
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DOI：
10.1111/j.1365-2966.2010.16991.x
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发表时间：
2010-10-01
影响因子：
4.8
通讯作者：
Frenk, C. S.
中科院分区：
文献类型：
--
作者：
Bower, R. G.;Vernon, I.;Frenk, C. S.
半解析模型是研究星系形成的有力工具。然而，这些模型不可避免地涉及大量约束不佳的参数，必须对这些参数进行调整，以提供与观测到的宇宙可接受的匹配。在本文中，我们着手量化观测数据集对模型参数的约束程度。通过揭示参数空间中的简并性，我们有望更好地理解数据所探测的关键物理过程。我们采用新颖的数学方法来探索半解析半解析模型的参数空间。我们的研究基于Bower等人版本的galform，采用相同的方法，根据与局部b(J)和K亮度函数的可接受匹配来选择模型参数。由于galform模型本质上是近似的，因此在决定匹配是否可以接受时，我们显式地包括一个模型差异项。该模型包含16个参数，这些参数受到我们之前对星系形成过程的理解的限制很少，并且可以在合理的范围内进行合理的调整。我们使用模型仿真器技术来研究这个参数空间，构造了一个可以在参数空间中任意点快速评估的galform模型的贝叶斯近似。仿真器返回galform模型的期望和不确定性，使我们能够消除参数空间的区域，其中galform运行不可能匹配亮度函数数据。通过结合连续的模拟波，我们表明只有0.26%的初始体积是值得进一步探索的。然而，在这个区域内，我们表明，Bower等人的模型只是模型参数扩展子空间中的一种选择，它可以为亮度函数数据提供同样可接受的拟合。我们探索这个区域的几何形状，并开始探索这个分析所暴露的参数之间的物理联系。我们还考虑了增加额外观测数据以进一步约束参数空间的影响。我们看到，Bower等人模型中存在的已知张力导致成功参数空间的进一步减小。
Semi-analytic models are a powerful tool for studying the formation of galaxies. However, these models inevitably involve a significant number of poorly constrained parameters that must be adjusted to provide an acceptable match to the observed Universe. In this paper, we set out to quantify the degree to which observational data sets can constrain the model parameters. By revealing degeneracies in the parameter space we can hope to better understand the key physical processes probed by the data. We use novel mathematical techniques to explore the parameter space of the galform semi-analytic model. We base our investigation on the Bower et al. version of galform, adopting the same methodology of selecting model parameters based on an acceptable match to the local b(J) and K luminosity functions. Since the galform model is inherently approximate, we explicitly include a model discrepancy term when deciding if a match is acceptable or not. The model contains 16 parameters that are poorly constrained by our prior understanding of the galaxy formation processes and that can plausibly be adjusted between reasonable limits. We investigate this parameter space using the Model Emulator technique, constructing a Bayesian approximation to the galform model that can be rapidly evaluated at any point in parameter space. The emulator returns both an expectation for the galform model and an uncertainty which allows us to eliminate regions of parameter space in which it is implausible that a galform run would match the luminosity function data. By combining successive waves of emulation, we show that only 0.26 per cent of the initial volume is of interest for further exploration. However, within this region we show that the Bower et al. model is only one choice from an extended subspace of model parameters that can provide equally acceptable fits to the luminosity function data. We explore the geometry of this region and begin to explore the physical connections between parameters that are exposed by this analysis. We also consider the impact of adding additional observational data to further constrain the parameter space. We see that the known tensions existing in the Bower et al. model lead to a further reduction in the successful parameter space.