GraphShed: A Data-derived Graph-based Watershed Group-finder
- 1Shahid Beheshti University
- 2Institute for Research in Fundamental Sciences (IPM)
- 3The University of Lahore
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.
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BibTeX
@article{ghafour2026graphshed,
title = {{GraphShed: A Data-derived Graph-based Watershed Group-finder}},
author = {P. Ghafour and S. Ansarifard and M. H. Jalali Kanafi and S. M. S. Movahed},
journal = {The Astrophysical Journal},
year = {2026},
month = oct,
doi = {10.3847/1538-4357/aea8fa},
url = {https://iopscience.iop.org/article/10.3847/1538-4357/aea8fa},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - GraphShed: A Data-derived Graph-based Watershed Group-finder
AU - P. Ghafour
AU - S. Ansarifard
AU - M. H. Jalali Kanafi
AU - S. M. S. Movahed
PY - 2026
DA - 2026/10/27
JO - The Astrophysical Journal
DO - 10.3847/1538-4357/aea8fa
UR - https://iopscience.iop.org/article/10.3847/1538-4357/aea8fa
AB - 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.
SN - 1538-4357
SN - 0004-637X
ER -