We use a large $N$-body simulation to study the relation of the structural properties of dark matter halos to their assembly history and environment. The complexity of individual halo assembly histories can be well described by a small number of principal components (PCs), which, compared to formation times, provide a more complete description of halo assembly histories and have a stronger correlation with halo structural properties. Using decision trees built with the random ensemble method, we find that about $60\%$, $10\%$, and $20\%$ of the variances in halo concentration, axis ratio, and spin, respectively, can be explained by combining four dominating predictors: the first PC of the assembly history, halo mass, and two environment parameters. Halo concentration is dominated by halo assembly. The local environment is found to be important for the axis ratio and spin but is degenerate with halo assembly. The small percentages of the variance in the axis ratio and spin that are explained by known assembly and environmental factors suggest that the variance is produced by many nuanced factors and should be modeled as such. The relations between halo intrinsic properties and environment are weak compared to their variances, with the anisotropy of the local tidal field having the strongest correlation with halo properties. Our method of dimension reduction and regression can help simplify the characterization of the halo population and clarify the degeneracy among halo properties.

中文翻译：

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将暗物质晕的结构与其组装和环境相关联

我们使用大型 $N$-body 模拟来研究暗物质晕的结构特性与其组装历史和环境之间的关系。单个晕组装历史的复杂性可以通过少量的主成分 (PC) 来很好地描述，与形成时间相比，这些主成分提供了对晕组装历史的更完整描述，并且与晕结构特性具有更强的相关性。使用随机集成方法构建的决策树，我们发现光晕浓度、轴比和自旋的方差分别约为 $60\%$、$10\%$ 和 $20\%$，可以通过组合四个主要预测因素：组装历史的第一个 PC、光晕质量和两个环境参数。晕集中由晕组装支配。发现局部环境对轴比和自旋很重要，但随着光环组装而退化。由已知组装和环境因素解释的轴比和自旋中的小百分比方差表明方差是由许多细微差别的因素产生的，应该这样建模。晕内在特性与环境之间的关系与其方差相比较弱，局部潮汐场的各向异性与晕特性的相关性最强。我们的降维和回归方法可以帮助简化晕群的表征并阐明晕属性之间的简并性。由已知组装和环境因素解释的轴比和自旋中的小百分比方差表明方差是由许多细微差别的因素产生的，应该这样建模。晕内在属性与环境之间的关系与其方差相比较弱，局部潮汐场的各向异性与晕属性的相关性最强。我们的降维和回归方法可以帮助简化晕群的表征并阐明晕属性之间的简并性。由已知的组装和环境因素解释的轴比和自旋中的小百分比方差表明方差是由许多细微差别的因素产生的，应该这样建模。晕内在特性与环境之间的关系与其方差相比较弱，局部潮汐场的各向异性与晕特性的相关性最强。我们的降维和回归方法可以帮助简化晕群的表征并阐明晕属性之间的简并性。局部潮汐场的各向异性与晕属性的相关性最强。我们的降维和回归方法可以帮助简化晕群的表征并阐明晕属性之间的简并性。局部潮汐场的各向异性与晕属性的相关性最强。我们的降维和回归方法可以帮助简化晕群的表征并阐明晕属性之间的简并性。