GraphShed: A Data-derived Graph-based Watershed Group-finder

Abstract This study introduces GraphShed, a data-derived group-finder that applies top-down watershed segmentation to Voronoi-induced graphs, identifying galaxy systems directly from the density field via a GraphShed-derived linking length, with no density thresholds or tunable parameters. A GraphShed galaxy group catalog compared to a friends-of-friends (FoF) catalog is built from the IllustrisTNG100-1 simulation with a box size of ∼75 Mpc h −1 yielding 1067 and 987 systems, respectively. The GraphShed-derived linking length adapts to the global clustering power of the sample, varying by ∼18% relative to FoF across different sample selections; thus, catalog differences originate in the watershed segmentation. A cross-catalog comparison shows that ∼58% of FoF systems are identically reproduced by GraphShed, ∼5% are completely removed, and the remainder are partially shaved and/or split into multiple systems. While the M 200 distributions of the two catalogs are statistically consistent, other structural properties including, R 200 , sphericity, compactness, spin, and centroid shift, differ significantly in at least some richness ranges. The unweighted two-point correlation function of GraphShed systems exhibits a higher amplitude on small scales, r ≲ 1 Mpc h −1 and agrees with FoF for r ≳ 5 Mpc h −1 . A velocity-based classification reveals that GraphShed resolves more interacting pairs than FoF, demonstrating its ability to distinguish nearby overdense structures that position-only methods merge into single systems. These results demonstrate that GraphShed preserves cosmological statistics while providing a more resolved detection of galaxy systems and their dynamical interactions.