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Cosmological simulations are useful tools for studying the evolution ofgalaxies, and it is critical to accurately identify galaxies and their halosfrom raw simulation data. The friends-of-friend (FoF) algorithm has been widelyadopted for this purpose because of its simplicity and expandability to higherdimensions. However, it is cost-inefficient when applied to high-resolutionsimulations because standard FoF implementation leads to too many distancecalculations in dense regions. We confirm this through our exercise of applyingthe 6-dimensional (6D) FoF galaxy finder code, VELOCIraptor (Elahi et al.2019), on the NewHorizon simulation (Dubois et al. 2021). The high particleresolution of NewHorizon ($M_{\rm star} \sim 10^4 M_{\odot}$) allows a largecentral number density ($10^{6}\,{\rm kpc}^{-3}$) for typical galaxies,resulting in a few days to weeks of galaxy searches for just one snapshot. Evenworse, we observed a significant decrease in the FoF performance in thehigh-dimensional 6D searches: "the curse of dimensionality" problem. Toovercome these issues, we have developed several implementations that can bereadily applied to any tree-based FoF code. They include limiting visits totree nodes, re-ordering the list of particles for searching neighbor particles,and altering the tree structure. Compared to the run with the original code,the new run with these implementations results in the identical galaxydetection with the ideal performance, $O(N \log{N})$, $N$ being the number ofparticles in a galaxy -- with a speed gain of a factor of 2700 in 3D or 12 in6D FoF search.

Performance Enhancement of Tree-based Friends-of-friend Galaxy-finder for High-resolution Simulations of Galaxy Formation