标题： 晕族统计的收敛性：基于无尺度模拟的Rockstar与CompaSO代码对比 显示英文标题

标题： Convergence of halo statistics: code comparison between Rockstar and CompaSO using scale-free simulations

摘要： 在本研究中，我们对 Rockstar 和 CompaSO 进行了 halo 探测器代码对比。基于我们之前旨在通过利用用 Abacus 运行的大规模（最高达$N=4096^3$）尺度不变宇宙学模拟来量化$N$体模拟分辨率的分析，我们将重点放在由上述两种算法选择的 halo 中心的质量函数（HMF）、双点相关函数（2PCF）以及平均径向双粒子速度的收敛性上。我们确定了 Rockstar 和 CompaSO 在质量函数上的$1\%$精度水平收敛，以及平均双粒子速度（以及 2PCF）上的$2\%$精度水平收敛。在小尺度和小质量下，我们发现 Rockstar 表现出更大的自相似性，并且还强调了 CompaSO halo 的合并树后处理对其收敛性所起的作用。最后，我们给出了以每个 halo 的最小粒子数表示的分辨率限制，这种形式可以直接外推到 LCDM 中。 显示英文摘要

摘要： In this study, we perform a halo-finder code comparison between Rockstar and CompaSO. Based on our previous analysis aiming at quantifying resolution of $N$-body simulations by exploiting large (up to $N=4096^3$) simulations of scale-free cosmologies run using Abacus, we focus on convergence of the HMF, 2PCF and mean radial pairwise velocities of halo centres selected with the aforementioned two algorithms. We establish convergence, for both Rockstar and CompaSO, of mass functions at the $1\%$ precision level and of the mean pairwise velocities (and also 2PCF) at the $2\%$ level. At small scales and small masses, we find that Rockstar exhibits greater self-similarity, and we also highlight the role played by the merger-tree post-processing of CompaSO halos on their convergence. Finally, we give resolution limits expressed as a minimum particle number per halo in a form that can be directly extrapolated to LCDM.