Automated Detection of Voids in Redshift Surveys

We present a new void search algorithm for automated detection of voids in three-dimensional redshift surveys. Based on a model in which the main features of the large-scale structure (LSS) of the universe are voids and walls, we classify the galaxies into wall galaxies and field galaxies, and we define voids as continuous volumes that are devoid of any wall galaxies. Field galaxies are allowed within the voids. The algorithm makes no assumptions regarding the shapes of the voids, and the only constraint that is imposed is that the voids are always thicker than a preset limit, thus eliminating connections between adjacent voids through small breaches in the walls. By appropriate scaling of the parameters with the selection function, this algorithm can be used to analyze flux-limited surveys. We test the algorithm on Voronoi tessellations and apply it to the SSRS2 survey to derive the spectrum of void sizes and other void properties. We find that the average diameter of a void is 37 ± 8 h-1 Mpc. We suggest the usage of this fully automated algorithm to derive a quantitative description of the voids, as another tool in describing the LSS of the universe and for comparison with numerical simulations.