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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2604.08855 |
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| _version_ | 1866908950988849152 |
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| author | Rodriguez-Meza, Mario A. Moreno, Eladio Aviles, Alejandro Niz, Gustavo |
| author_facet | Rodriguez-Meza, Mario A. Moreno, Eladio Aviles, Alejandro Niz, Gustavo |
| contents | 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). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_08855 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | cTreeBalls: a fast 3-point correlation function code for clustering measurements Rodriguez-Meza, Mario A. Moreno, Eladio Aviles, Alejandro Niz, Gustavo Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics 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). |
| title | cTreeBalls: a fast 3-point correlation function code for clustering measurements |
| topic | Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics |
| url | https://arxiv.org/abs/2604.08855 |