通过扩充N体合并树实现星系形成模型的收敛
Achieving Convergence in Galaxy Formation Models by Augmenting N-body Merger Trees
摘要：
在一个分层的、冷的暗物质宇宙中精确模拟星系形成，需要使用足够高分辨率的合并树来获得星系预测属性的收敛。当半解析星系形成模型应用于宇宙学N体模拟合并树时，通常情况下，这些树的分辨率不足以给出收敛的星系特性。我们展示了一种通过嫁接具有更高分辨率的蒙特卡罗合并树的分支来增强N体合并树分辨率的方法，但这些分支与N体树中预先存在的分支一致。我们表明，这种方法会导致收敛的星系属性。
英文摘要：
Accurate modeling of galaxy formation in a hierarchical, cold dark matter universe requires the use of sufficiently high-resolution merger trees to obtain convergence in the predicted properties of galaxies. When semi-analytic galaxy formation models are applied to cosmological N-body simulation merger trees, it is often the case that those trees have insufficient resolution to give converged galaxy properties. We demonstrate a method to augment the resolution of N-body merger trees by grafting in branches of Monte Carlo merger trees with higher resolution, but which are consistent with the pre-existing branches in the N-body tree. We show that this approach leads to converged galaxy properties.
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