We introduce phew (Parallel HiErarchical Watershed), a new segmentation algorithm to detect structures in astrophysical fluid simulations, and its implementation into the adaptive mesh refinement (AMR) code ramses. phew works on the density field defined on the adaptive mesh, and can thus be used on the gas density or the dark matter density after a projection of the particles onto the grid. The algorithm is based on a ‘watershed’ segmentation of the computational volume into dense regions, followed by a merging of the segmented patches based on the saddle point topology of the density field. phew is capable of automatically detecting connected regions above the adopted density threshold, as well as the entire set of substructures within. Our algorithm is fully parallel and uses the MPI library. We describe in great detail the parallel algorithm and perform a scaling experiment which proves the capability of phew to run efficiently on massively parallel systems. Future work will add a particle unbinding procedure and the calculation of halo properties onto our segmentation algorithm, thus expanding the scope of phew to genuine halo finding.

中文翻译：

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PHEW：三维AMR数据集的并行分割算法

我们介绍了phew（并行HiErarchical分水岭），一种新的分割算法，用于检测天体流体模拟中的结构，并将其实现到自适应网格细化（AMR）代码组中。phew在自适应网格上定义的密度场上起作用，因此可以在将粒子投影到网格上之后用于气体密度或暗物质密度。该算法基于将计算量“分水岭”分割为密集区域，然后基于密度场的鞍点拓扑合并分割后的补丁。phew能够自动检测超出采用的密度阈值的连接区域，以及其中的整个子结构集。我们的算法是完全并行的，并使用MPI库。我们将详细描述并行算法，并进行缩放实验，以证明phew在大规模并行系统上有效运行的能力。未来的工作将在我们的分割算法上增加一个粒子解绑程序和光晕特性的计算，从而将的范围扩展到真正的光环发现。