Populating dark matter haloes with galaxies: comparing the 2dFGRS with mock galaxy redshift surveys
Populating dark matter haloes with galaxies: comparing the 2dFGRS with mock galaxy redshift surveys
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DOI：
10.1111/j.1365-2966.2004.07744.x
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发表时间：
2003-03
影响因子：
4.8
通讯作者：
Xiaohu Yang;Xiaohu Yang;H. Mo;H. Mo;Y. Jing;F. V. D. Bosch;Y. Chu
中科院分区：
文献类型：
--
作者：
Xiaohu Yang;Xiaohu Yang;H. Mo;H. Mo;Y. Jing;F. V. D. Bosch;Y. Chu
在最近的两篇论文中，我们开发了一种强大的技术，将星系的分布与暗物质晕的分布联系起来，将晕占据数视为星系光度和类型的函数。在本文中，我们使用这些分布函数填充暗物质晕在高分辨率N体模拟的标准Lambda CDM宇宙学与欧米茄（m）= 0.3，欧米茄（λ）= 0.7和西格玛（8）= 0.9。将100 h（-1）Mpc和300 h（-1）Mpc的模拟盒与512 3个粒子堆叠在一起，我们构建了红移z = 0.2的模拟星系红移巡天，其数值分辨率保证完整性下降到0.01L*。我们使用这些模拟调查来调查各种聚类统计。预测的二维相关函数xi（r（p），pi）揭示了红移空间畸变的明显特征。由xi（r（p），pi）导出的不同光度和类型星系的投影相关函数，在大于3 h（-1）Mpc的尺度上与观测结果很好地匹配。然而，在较小的尺度上，该模型高估了聚类能力约2倍。在小尺度上模拟“上帝之指”效应表明，标准的Lambda CDM模型预测的成对速度离散（PVD）近似于400 km s（-1），在预测的成对分离近似于1 h（-1）Mpc时过高。大质量晕中的强速度偏差，B（vel）相当于sigma（gal）/sigma（dm）--近似于0.6（其中sigma（gal）和sigma（dm）分别是星系和暗物质粒子的速度分散），可以将预测的PVD降低到观测水平，但无助于解决小尺度上聚集能力的过度预测。只有当团簇的平均质光比为1000（M/L）时，才能在标准Lambda CDM模型中获得一致的结果。在B波段。或者，正如我们通过一个简单的近似所表明的那样，一个σ（δ）近似或等于0.75的Lambda CDM模型也可以重现观测结果。我们讨论了我们的结果，根据最近的WMAP结果和约束σ（8）独立于其他观测。
In two recent papers, we developed a powerful technique to link the distribution of galaxies to that of dark matter haloes by considering halo occupation numbers as a function of galaxy luminosity and type. In this paper we use these distribution functions to populate dark matter haloes in high-resolution N-body simulations of the standard LambdaCDM cosmology with Omega(m) = 0.3, Omega(Lambda) = 0.7 and sigma(8) = 0.9. Stacking simulation boxes of 100 h(-1) Mpc and 300 h(-1) Mpc with 512 3 particles each we construct mock galaxy redshift surveys out to a redshift of z = 0.2 with a numerical resolution that guarantees completeness down to 0.01L*. We use these mock surveys to investigate various clustering statistics. The predicted two-dimensional correlation function xi(r(p), pi) reveals clear signatures of redshift space distortions. The projected correlation functions for galaxies with different luminosities and types, derived from xi(r(p), pi), match the observations well on scales larger than similar to3 h(-1) Mpc. On smaller scales, however, the model overpredicts the clustering power by about a factor two. Modelling the 'finger-of-God' effect on small scales reveals that the standard LambdaCDM model predicts pairwise velocity dispersions (PVD) that are similar to400 km s(-1) too high at projected pair separations of similar to1 h(-1) Mpc. A strong velocity bias in massive haloes, with b(vel) equivalent to sigma(gal)/sigma(dm) - similar to0.6 (where sigma(gal) and sigma(dm) are the velocity dispersions of galaxies and dark matter particles, respectively) can reduce the predicted PVD to the observed level, but does not help to resolve the overprediction of clustering power on small scales. Consistent results can be obtained within the standard LambdaCDM model only when the average mass-to-light ratio of clusters is of the order of 1000 (M/L). in the B-band. Alternatively, as we show by a simple approximation, a LambdaCDM model with sigma(8) similar or equal to 0.75 may also reproduce the observational results. We discuss our results in light of the recent WMAP results and the constraints on sigma(8) obtained independently from other observations.