论文标题
关于银河调查中三点相关函数的快速随机采样和其他属性
On the Fast Random Sampling and Other Properties of the Three Point Correlation Function in Galaxy Surveys
论文作者
论文摘要
在即将到来的大型星系调查中，高阶统计数据将为通常的两个点统计数据提供互补信息。离散数据计数三角形配置的三个点相关函数（3CPF）的低方差估计量与顶点混合数据和随机目录。大密度随机目录用于减少射击噪声，这比纯数据直方图的计算成本高出一个或两个数量级。在本文中，我们探讨了在不使用随机目录的情况下，在周期盒中的各向同性3PCF随机抽样项的时间缩短。在第一种方法中，基于汉密尔顿著名的两个点估计器的构建，我们使用临时的两个点相关项，而对于第二个过程，我们从几何观点构造了操作员，使用两个侧面及其开头来描述3pcf三角形配置。我们将最后一个结果映射到数值或分析上的三个三角侧基础上，并表明后一种方法在应用于合成数据时性能最好。此外，我们详细介绍了超越周期框，讨论其他低方差n点估计器，并提出了有用的3PCF可视化方案。
In the forthcoming large volume galaxy surveys higher order statistics will provide complementary information to the usual two point statistics. Low variance estimators of the Three Point Correlation Function (3CPF) of discrete data count triangle configurations with vertices mixing data and random catalogues. Large density random catalogues are used to reduce the shot noise, which leads to a computational cost of one or two orders of magnitude more than the pure data histogram. In this paper, we explore time reductions of the isotropic 3PCF random sampling terms in periodic boxes without using random catalogues. In the first approach, based on Hamilton's construction of his famous two point estimator, we use an ad-hoc two point correlation term, while for the second procedure we construct the operators from a geometrical viewpoint, using two sides and their opening angle to describe the 3PCF triangle configurations. We map the last result to the three triangle side basis either numerically or analytically, and show that the latter approach performs best when applied to synthetic data. Moreover, we elaborate on going beyond periodic boxes, discuss other low variance n-point estimators and present useful 3PCF visualization schemes.
