论文标题

肌肉 - 提高了物质领域的近似值,并扩展了新闻编式形式主义和拉格朗日扰动理论

MUSCLE-UPS: Improved Approximations of the Matter Field with the Extended Press-Schechter Formalism and Lagrangian Perturbation Theory

论文作者

Tosone, Federico, Neyrinck, Mark C., Granett, Benjamin R., Guzzo, Luigi, Vittorio, Nicola

论文摘要

Lagrangian算法模拟冷暗物质的演变(CDM)是生成大型模拟Halo目录的宝贵工具。 In this paper, we first show that the main limitation of current semi-analytical schemes to simulate the displacement of CDM is their inability to model the evolution of overdensities in the initial density field, a limit that can be circumvented by detecting halo particles in the initial conditions.因此,我们提出了“使用Press-Schechter的多尺度球形崩溃的Lagrangian进化”(肌肉 - 向上),这是一种新方案,在大尺度上重现了Lagrangian扰动理论的结果,同时改善了小尺度上过度繁殖的建模。在肌肉激增中,我们将扩展的新闻和Schechter(EPS)形式主义适应位移领域的拉格朗日算法。对于超过半径$ r $的密度倒塌阈值的区域,我们考虑了半径$ r $倒塌的所有粒子。 Exploiting a multi-scale smoothing of the initial density, we build a halo catalogue on the fly by optimizing the selection of halo candidates.这使我们能够生成具有光晕质量函数的密度字段,该密度函数与$ n $ body模拟测量的密度函数相匹配。我们进一步将每个光晕中的粒子聚集在一起,在一个轮廓中,提供了基于Lagrangian模型的数字实现。与以前的半分析拉格朗日方法相比,我们发现肌肉升高可改善概率密度函数(PDF),功率谱以及与$ n $ body结果的概率密度函数(PDF),功率谱和跨相关性的恢复。

Lagrangian algorithms to simulate the evolution of cold dark matter (CDM) are invaluable tools to generate large suites of mock halo catalogues. In this paper, we first show that the main limitation of current semi-analytical schemes to simulate the displacement of CDM is their inability to model the evolution of overdensities in the initial density field, a limit that can be circumvented by detecting halo particles in the initial conditions. We thus propose `MUltiscale Spherical Collapse Lagrangian Evolution Using Press-Schechter' (muscle-ups), a new scheme that reproduces the results from Lagrangian perturbation theory on large scales, while improving the modelling of overdensities on small scales. In muscle-ups, we adapt the extended Press and Schechter (EPS) formalism to Lagrangian algorithms of the displacement field. For regions exceeding a collapse threshold in the density smoothed at a radius $R$, we consider all particles within a radius $R$ collapsed. Exploiting a multi-scale smoothing of the initial density, we build a halo catalogue on the fly by optimizing the selection of halo candidates. This allows us to generate a density field with a halo mass function that matches one measured in $N$-body simulations. We further explicitly gather particles in each halo together in a profile, providing a numerical, Lagrangian-based implementation of the halo model. Compared to previous semi-analytical Lagrangian methods, we find that muscle-ups improves the recovery of the statistics of the density field at the level of the probability density function (PDF), the power spectrum, and the cross correlation with the $N$-body result.

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