The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-098)
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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 098 of the 2048³ resolution collection.
本研究展示基于一致性Λ冷暗物质(LCDM)模型构建的"Cosmogrid"宇宙学N体模拟(N-body simulation)套件的相关结果。本次Cosmogrid模拟在边长为30百万秒差距(Mpc)的立方体盒子中开展,共包含2048³个粒子。单个粒子质量为1.28×10^5倍太阳质量(Msun),该质量分辨率足以解析超暗矮星系。研究发现,晕质量函数与希思-托门(Sheth & Tormen)拟合函数在低至~10^7倍太阳质量的范围内均保持良好一致性。本研究对三个质量最大的星系群级晕结构开展了球对称平均密度剖面分析,这三个晕均包含至少1.7亿个粒子。在最内侧半径处,这些密度剖面的斜率相较于-1更为平缓。同时研究发现,晕的集中度与质量存在显著相关性。集中度参数的质量依赖关系无法用单一幂律函数描述,但纳瓦罗等人(Navarro et al.)基于普雷斯-谢赫特(Press-Schechter)理论提出的简单模型与该依赖关系吻合良好。自旋参数则与晕质量无显著相关性。对于质量大于~10^8倍太阳质量的晕结构,其集中度与自旋参数的概率分布函数均可通过对数正态分布得到良好拟合。次晕丰度同样依赖于宿主晕质量:星系级晕的次晕数量比质量约为10^11倍太阳质量的晕多50%。本数据集属于2048³分辨率模拟序列的第098号快照。
提供机构:
Leiden University
创建时间:
2019-04-28



