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Superclusters are a convenient way to partition and characterize the largescale structure of the Universe. In this Letter we explore the advantages ofdefining superclusters as watershed basins in the divergence velocity field. Weapply this definition on diverse datasets generated from linear theory andN-body simulations, with different grid sizes, smoothing scales and types oftracers. From this framework emerges a linear scaling relation between theaverage supercluster size and the autocorrelation length in the divergencefield, a result that holds for one order of magnitude from 10 Mpc/h up to 100Mpc/h. These results suggest that the divergence-based definition provides arobust context to quantitatively compare results across different observationalor computational frameworks. Through its connection with linear theory, it canalso facilitate the exploration of how supercluster properties depend oncosmological parameters, paving the way to use superclusters as cosmologicalprobes.

Superclusters from velocity divergence fields