This study is the first in a series in which we analyse the structure and topology of the Cosmic Web as traced by the Sloan Digital Sky Survey (SDSS). The main issue addressed in the present study is the translation of the irregularly distributed discrete spatial data in the galaxy redshift survey into a representative density field. The density field will form the basis for a statistical, topological and cosmographic study of the cosmic density field in our Local Universe. We investigate the ability of three reconstruction techniques to analyse and investigate web-like features and geometries in a discrete distribution of objects. The three methods are the linear Delaunay Tessellation Field Estimator (DTFE), its higher order equivalent Natural Neighbour Field Estimator (NNFE) and a version of the Kriging interpolation adapted to the specific circumstances encountered in galaxy redshift surveys, the Natural Lognormal Kriging technique. DTFE and NNFE are based on the local geometry defined by the Voronoi and Delaunay tessellations of the galaxy distribution. The three reconstruction methods are analysed and compared using mock magnitude- and volume-limited SDSS redshift surveys, obtained on the basis of the Millennium simulation. We investigate error trends, biases and the topological structure of the resulting fields, concentrating on the void population identified by the Watershed Void Finder. Environmental effects are addressed by evaluating the density fields on a range of Gaussian filter scales. Comparison with the void population in the original simulation yields the fraction of false void mergers and false void splits. In most tests DTFE, NNFE and Kriging have largely similar density and topology error behaviour. Cosmetically, higher order NNFE and Kriging methods produce more visually appealing reconstructions. Quantitatively, however, DTFE performs better, even while being computationally far less demanding. A successful recovery of the void population on small scales appears to be difficult, while the void recovery rate improves significantly on scales >3 h−1 Mpc. A study of small-scale voids and the void galaxy population should therefore be restricted to the local Universe, out to at most 100 h−1 Mpc.
- large-scale structure of Universe
- methods: data analysis
- methods: numerical
- methods: statistical
- cosmology: observations