A robust public catalogue of voids and superclusters in the SDSS Data
  Release 7 galaxy surveys
  The study of the interesting cosmological properties of voids in the Universe
depends on the efficient and robust identification of such voids in galaxy
redshift surveys. Recently, Sutter et al. (2012) have published a public
catalogue of voids in the Sloan Digital Sky Survey Data Release 7 main galaxy
and luminous red galaxy samples, using the void-finding algorithm ZOBOV, which
is based on the watershed transform. We examine the properties of this
catalogue and show that it suffers from several problems and inconsistencies,
including the identification of some extremely overdense regions as voids. As a
result, cosmological results obtained using this catalogue need to be
reconsidered. We provide instead an alternative, self-consistent, public
catalogue of voids in the same galaxy data, obtained from using an improved
version of the same watershed transform algorithm. We provide a more robust
method of dealing with survey boundaries and masks, as well as with a radially
varying selection function, which means that our method can be applied to any
other survey. We discuss some basic properties of the voids thus discovered,
and describe how further information may be obtained from the catalogue. In
addition, we apply an inversion of the algorithm to the same data to obtain a
corresponding catalogue of large-scale overdense structures, or
"superclusters". Our catalogues are available for public download at
www.hip.fi/nadathur/download/dr7catalogue.
