暗物质晕向高阶的组装偏向
The assembly bias of dark matter haloes to higher orders
摘要：
我们使用一个非常大的体积（$2.4h^{-3}{\rm Gpc}^{3}$），高分辨率的N体模拟来测量高阶集群的暗物质晕的质量和内部结构的函数。由于大的模拟量和使用一种新的“交叉矩”计数在细胞技术，抑制离散噪声，我们能够测量聚类的晕对应于罕见的峰值比以前的研究是可能的;最罕见的晕，我们测量的方差是100倍以上的集群比暗物质。我们能够提取，第一次，晕偏置参数从线性到四阶。对于测量的所有订单，我们发现，偏置参数是一个强大的功能的质量晕更大规模的特征质量$M_{*}$。目前，没有理论模型能够精确地再现这种质量依赖性。我们发现，偏置参数也依赖于内部结构的晕到四阶。对于质量大于$M_{*}$的晕，我们发现，更集中的晕比不太集中的更弱的集群。我们没有看到集群与质量$M<M_{*}$晕浓度的依赖性，这是相反的趋势，在文献中报道的隔离晕时，其形成时间。我们的研究结果是不敏感的晕是否标记的朋友的朋友组发现者返回的总质量或最大规模的子结构的质量。这意味着我们的结论不是特定选择的群体发现算法的人工制品。我们的研究结果将提供重要的投入星系集群的理论模型。
英文摘要：
We use an extremely large volume ($2.4h^{-3}{\rm Gpc}^{3}$), high resolution N-body simulation to measure the higher order clustering of dark matter haloes as a function of mass and internal structure. As a result of the large simulation volume and the use of a novel ``cross-moment'' counts-in-cells technique which suppresses discreteness noise, we are able to measure the clustering of haloes corresponding to rarer peaks than was possible in previous studies; the rarest haloes for which we measure the variance are 100 times more clustered than the dark matter. We are able to extract, for the first time, halo bias parameters from linear up to fourth order. For all orders measured, we find that the bias parameters are a strong function of mass for haloes more massive than the characteristic mass $M_{*}$. Currently, no theoretical model is able to reproduce this mass dependence closely. We find that the bias parameters also depend on the internal structure of the halo up to fourth order. For haloes more massive than $M_{*}$, we find that the more concentrated haloes are more weakly clustered than the less concentrated ones. We see no dependence of clustering on concentration for haloes with masses $M<M_{*}$; this is contrary to the trend reported in the literature when segregating haloes by their formation time. Our results are insensitive to whether haloes are labelled by the total mass returned by the friends-of-friends group finder or by the mass of the most massive substructure. This implies that our conclusions are not an artefact of the particular choice of group finding algorithm. Our results will provide important input to theoretical models of galaxy clustering.
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