📝 SummarXiv

Abstract

We introduce Nessie, a galaxy group finder implemented in Rust and distributed as both a Python and R package. Nessie employs the friends-of-friends (FoF) algorithm and requires only on-sky position and redshift as input, making it immediately applicable to surveys that lack a well-defined luminosity function. We implement several algorithmic optimizations including binary search and k-d tree pre-selection that significantly improve performance by reducing unnecessary galaxy pair checks. To validate the accuracy of Nessie, we tune its parameters using a suite of GALFORM mock lightcones and achieve a strong Figure of Merit. We further demonstrate its reliability by applying it to both the GAMA and SDSS surveys, where it produces group catalogues consistent with those in the literature. Additional functionality is included for comparison with simulations and mock catalogues. Benchmarking on a standard MacBook Pro (M3 chip with 11 cores) shows that version 1 of Nessie can process about 1 million galaxies in around 10 seconds, highlighting its speed and suitability for next-generation redshift surveys.