A cosmic watershed: the WVF void detection technique

By Erwin Platen, Rien van de Weygaert, Bernard J. T. Jones. 2007

230 citations recorded by the source corpus.

On megaparsec scales the Universe is permeated by an intricate filigree of clusters, filaments, sheets and voids, the cosmic web. For the understanding of its dynamical and hierarchical history it is crucial to identify objectively its complex morphological components. One of the most characteristic aspects is that of the dominant underdense voids, the product of a hierarchical process driven by the collapse of minor voids in addition to the merging of large ones. In this study we present an objective void finder technique which involves a minimum of assumptions about the scale, structure and shape of voids. Our void finding method, the watershed void finder (WVF), is based upon the watershed transform, a well-known technique for the segmentation of images. Importantly, the technique has the potential to trace the existing manifestations of a void hierarchy. The basic watershed transform is augmented by a variety of correction procedures to remove spurious structure resulting from sampling noise. This study contains a detailed description of the WVF. We demonstrate how it is able to trace and identify, relatively parameter free, voids and their surrounding (filamentary and planar) boundaries. We test the technique on a set of kinematic Voronoi models, heuristic spatial models for a cellular distribution of matter. Comparison of the WVF segmentations of low-noise and high-noise Voronoi models with the quantitatively known spatial characteristics of the intrinsic Voronoi tessellation shows that the size and shape of the voids are successfully retrieved. WVF manages to even reproduce the full void size distribution function.

Subfields: Astronomy and Astrophysics, Ecology, Instrumentation

View Paper: https://www.semanticscholar.org/paper/7630a1133b49247702f231e2450912decfe715c4

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Citations in the corpus

zobov: a parameter-free void-finding algorithm (2007, methodology): “1 of Platen et al. (2007).”
Multiscale phenomenology of the cosmic web (2010, background): “Ultrahigh resolution N-body simulations show that even in the most underdense regions one can find systems of tenuous filaments extending along the whole physical extent of the voids (van de Weygaert & van Kampen 1993; Gottlöber et al. 2003; Platen et al. 2007).”
Connecting the cosmic web to the spin of dark haloes: implications for galaxy formation (2012, methodology): “Another interesting approach was followed by Platen et al. (2007, 2008) who used Watershed transforms to identify voids, filaments and walls.”
The persistent cosmic web and its filamentary structure I: Theory and implementation (2010, methodology): “The watershed technique (see Beucher & Lantujoul 1979; Roerdink & Meijster 2000) was first applied to this kind of problem by Platen et al. (2007) as a means of identifying voids in large-scale structures (see also Platen, van de Weygaert & Jones 2008; Colberg et al. 2008; Aragón-Calvo et al.…”
NEXUS: Tracing the cosmic web connection (2012, methodology): “The WT was introduced by Platen et al. (2007) as the basis of the Watershed Void Finder technique (Platen et al. 2007) which identifies cosmic voids with the watershed basins.”
Tracing the cosmic web (2017, methodology): “A typical example involves the delineation of underdense void basins in the large scale mass distribution by means of the Watershed Transform, in the form of the Watershed Void Finder (Platen et al. 2007) and ZOBOV (Neyrinck 2008).”
A Dynamical Classification of the Cosmic Web (2008, unknown): “41 35 v1 [ as tr oph ] 2 4 Se 2005; Gottlöber et al. 2003; Arbabi-Bidgoli & Müller 2002; Neyrinck 2008; Platen et al. 2007; Plionis & Basilakos 2002; Shandarin et al. 2006).”
Evolution of the cosmic web (2014, background): “This is a clear manifestation of the hierarchical distribution of voids, with smaller voids enclosed within larger underdense regions (van de Weygaert & van Kampen 1993; Sheth & van de Weygaert 2004; Platen et al. 2007; Aragon-Calvo et al. 2011; Aragon-Calvo & Szalay 2013; Rieder et al. 2013).”
The Aspen-Amsterdam void finder comparison project (2008, methodology): “The density field is adaptively smoothed by nearest neighbour median filtering (Platen et al. 2007).”