The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-185)
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https://repository.surfsara.nl/datasets/cosmogrid/276
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We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 185 of the 2048³ resolution collection.
我们呈现基于标准Λ冷暗物质模型(ΛCDM model)的‘Cosmogrid’宇宙学N体模拟套件的结果。Cosmogrid模拟在一个30百万秒差距(Mpc)的立方盒中进行,包含2048³个粒子。每个粒子的质量为1.28×10⁵太阳质量(Msun),足以解析超暗矮星系。我们发现,晕质量函数与Sheth&Tormen拟合函数在低至约10⁷太阳质量(Msun)的范围内具有良好的一致性。我们分析了三个质量最大的晕的球平均密度剖面,这些晕具有星系群尺度,且包含至少1.7亿个粒子。这些密度剖面的斜率在最内半径处变得比-1更平缓。我们还发现晕的浓度与质量之间存在明显的相关性。浓度参数的质量依赖性无法用单一幂律表示,但基于Navarro等人提出的Press-Schechter理论(Press-Schechter theory)的简单模型与这种依赖性具有合理的一致性。自旋参数与晕质量之间无明显相关性。对于质量大于约10⁸太阳质量(Msun)的晕,浓度和自旋的概率分布函数均能被对数正态分布很好地拟合。子晕丰度依赖于晕的质量。星系尺度的晕比约10¹¹太阳质量(Msun)的晕多50%的子晕。本数据集为2048³分辨率集合中的第185个快照。
提供机构:
Leiden University
创建时间:
2019-09-12



