论文标题
牛：Hessian Cosmic Web标识符的细丝查找器
COWS: A filament finder for Hessian cosmic web identifiers
论文作者
论文摘要
大规模的星系和物质分布通常是通过宇宙网络描述的，由空隙，床单，细丝和结组成。存在许多不同的食谱来识别此宇宙网络。在这里，我们将重点放在基于Hessian矩阵的分析的宇宙Web标识符上，并提出了一种称为宇宙Web骨架（Cows）的方法，将一组细胞单元格分为单个谨慎的细胞集合。具体而言，将变薄的算法应用于基于速度剪切张量的宇宙腹板（V-WEB），以识别丝的脊柱。这会导致一组具有明确定义的终点和长度的细丝。证实这些位于局部密度脊，并与基础速度场定义的适当方向对齐。还检查了这些弯曲的圆柱丝的径向密度谱以及其长度的分布。所有结果的鲁棒性都针对分辨率和V-WEB阈值进行检查。奶牛方法的代码已公开可用。
The large scale galaxy and matter distribution is often described by means of the cosmic web made up of voids, sheets, filaments and knots. Many different recipes exist for identifying this cosmic web. Here we focus on a sub-class of cosmic web identifiers, based on the analysis of the Hessian matrix, and proposed a method, called COsmic Web Skeleton (COWS), of separating a set of filaments cells into an ensemble of individual discreet filaments. Specifically, a thinning algorithm is applied to velocity shear tensor based cosmic web (V-web) to identify the spine of the filaments. This results in a set of filaments with well defined end-point and length. It is confirmed that these sit at local density ridges and align with the appropriate direction defined by the underlying velocity field. The radial density profile of these curved cylindrical filaments, as well as the distribution of their lengths is also examined. The robustness of all results is checked against resolution and the V-web threshold. The code for the COWS method has been made publicly available.
