Voids in the LCRS versus CDM Models

TL;DR

This study compares void size distributions in the LCRS galaxy survey with mock samples from various CDM models, revealing that galaxy biasing significantly influences void statistics more than differences in cosmological parameters.

Contribution

It introduces a method to analyze void sizes in galaxy surveys and compares observational data with mock simulations to assess the impact of galaxy biasing and cosmological models.

Findings

Void sizes scale with mean galaxy separation.

Galaxy biasing affects void size distribution more than cosmological differences.

Void coverage and correlation functions provide complementary insights.

Abstract

We have analyzed the distribution of void sizes in the two-dimensional slices of the Las Campanas Redshift Survey (LCRS). Fourteen volume-limited subsamples were extracted from the six slices to cover a large part of the survey and to test the robustness of the results against cosmic variance. Thirteen samples were randomly culled to produce homogeneously selected samples. We then studied the relationship between the cumulative area covered by voids and the void size as a property of the void hierarchy. We find that the distribution of void sizes scales with the mean galaxy separation, $\lambda$. In particular, we find that the size of voids covering half of the area is given by $D_{med} \approx \lambda + (12\pm3) \h^{-2}$Mpc. Next, by employing an environmental density threshold criterion to identify mock galaxies, we were able to extend this analysis to mock samples from dynamical $n$-body simulations of Cold Dark Matter (CDM) models. To reproduce the observed void statistics, overdensity thresholds of $\delta_{th} \approx 0 ... 1$ are necessary. We have compared standard (SCDM), open (OCDM), vacuum energy dominated ($\Lambda$CDM), and broken scale invariant CDM models (BCDM): we find that both the void coverage distribution and the two-point correlation function provide important and complementary information on the large-scale matter distribution. The dependence of the void statistics on the threshold criterion for the mock galaxy indentification shows that the galaxy biasing is more crucial for the void size distribution than are differences between the cosmological models.