论文标题
$ n $ - 点流模型：速度如何形状相关性在红移空间中的功能
The $n$-point streaming model: how velocities shape correlation functions in redshift space
论文作者
论文摘要
从第一原则开始，我们得出了将$ n $ - 点相关功能在实际和红移空间中函数相关联的基本方程。我们的结果将所谓的“流模型”概括为高阶统计：RedShift空间中的整个$ N $ - 点相关是其真实空间对应到的整体乘以$ n-1 $ n-1 $相对偏见线的关节概率密度。连接的$ n $ - 点相关函数的方程是通过递归应用通用流模型来减少$ n $来获得的。我们的结果精确地在遥远的观察者近似值内，并且完全独立于评估相关性的示踪剂的性质。为了关注三点统计，我们使用$ n $体体模拟来研究三胞胎中相对视线速度的相对视线速度的联合概率密度函数。在很大的范围内，我们发现这种分布大约是高斯，并且可以通过标准扰动理论准确地计算其力矩。我们使用这些信息来制定现象学三点高斯流媒体模型。通过在领先顺序上使用扰动理论来近似实际空间中的几个统计数据，从而获得了实际实现。尽管进行了简化，但在红移空间中对物质的3点相关函数的结果预测与模拟中执行的测量相当一致。我们讨论简化模型的局限性，并提出许多可能的改进。我们的结果在分析星系聚类分析中发现了直接应用，但也为基于动力学Sunyaev-Zel'Dovich效应的未来特殊速度调查和实验进行了研究的基础。
Starting from first principles, we derive the fundamental equations that relate the $n$-point correlation functions in real and redshift space. Our result generalises the so-called `streaming model' to higher-order statistics: the full $n$-point correlation in redshift-space is obtained as an integral of its real-space counterpart times the joint probability density of $n-1$ relative line-of-sight peculiar velocities. Equations for the connected $n$-point correlation functions are obtained by recursively applying the generalised streaming model for decreasing $n$. Our results are exact within the distant-observer approximation and completely independent of the nature of the tracers for which the correlations are evaluated. Focusing on 3-point statistics, we use an $N$-body simulation to study the joint probability density function of the relative line-of-sight velocities of pairs of particles in a triplet. On large scales, we find that this distribution is approximately Gaussian and that its moments can be accurately computed with standard perturbation theory. We use this information to formulate a phenomenological 3-point Gaussian streaming model. A practical implementation is obtained by using perturbation theory at leading order to approximate several statistics in real space. In spite of this simplification, the resulting predictions for the matter 3-point correlation function in redshift space are in rather good agreement with measurements performed in the simulation. We discuss the limitations of the simplified model and suggest a number of possible improvements. Our results find direct applications in the analysis of galaxy clustering but also set the basis for studying 3-point statistics with future peculiar-velocity surveys and experiments based on the kinetic Sunyaev-Zel'dovich effect.
