cTreeBalls：一种快速的三点相关函数代码用于聚类测量
cTreeBalls: a fast 3-point correlation function code for clustering measurements
AI总结：
cTreeBalls是一种用于测量二点和三点聚类统计的Python/C程序，能在10分钟内处理2亿多个HEALPix像素，适用于LSST数据的分析。
摘要：
cTreeBalls（简称cBalls）是一种有用的Python/C程序，用于测量（2,3）点聚类统计。cBalls能够高效计算超过2亿个HEALPix像素（全天空模拟，Nside=4096）的三点相关函数，耗时不到10分钟，可在单个高性能计算节点上完成，为即将到来的LSST数据提供可行的分析。它基于八叉树（Barnes & Hut, 1986）和k-d树算法（Bentley, 1975），并提供用户友好的接口，支持灵活的目录数据和测量结果的输入/输出（I/O），并通过外部参数文件进行配置，并通过增强的日志记录和警告/异常处理进行跟踪。为完整性和补充性，该程序还包含用于周期性盒子的两点聚类统计测量方法。cTreeBalls是为Dark Energy Science Collaboration（DESC）的Rubin Observatory Legacy Survey of Space and Time（LSST）开发的。
英文摘要：
cTreeBalls (cBalls for short) is a Python/C package useful to measure (2,3)-point clustering statistics. cBalls can efficiently calculate 3-point correlations of more than 200 million HEALPix pixels ( a full sky simulation with Nside = 4096) in less than 10 minutes on a single high-performance computing node, enabling a feasible analysis for the upcoming LSST data. It builds upon octree (Barnes & Hut, 1986) and kd-tree algorithms (Bentley, 1975), and supplies a user-friendly interface with flexible input/output (I/O) of catalogue data and measurement results, with the built program configurable through external parameter files and tracked through enhanced logging and warning/exception handling. For completeness and complementarity, methods for measuring two-point clustering statistics for periodic boxes are also included in the package. cTreeBalls was developed for its use in the Dark Energy Science Collaboration (DESC) of the Rubin Observatory Legacy Survey of Space and Time (LSST).
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