Clustering and Bias Measurements of SDSS Voids

TL;DR

This paper measures the clustering and bias of cosmic voids from SDSS data, revealing how void bias varies with size and demonstrating consistency with models, advancing their use in cosmology.

Contribution

First measurements of void clustering and bias from SDSS data, showing scale-independent bias for fixed sizes and validating model predictions without free parameters.

Findings

Void auto-correlation detected at 5-sigma significance for certain sizes.

Void bias decreases from 5.6 to below zero as radius increases.

Model predictions match observed void correlations without free parameters.

Abstract

Using a void catalog from the SDSS survey, we present the first measurements of void clustering and the corresponding void bias. Over the range 30-200 Mpc/h the void auto-correlation is detected at 5-sigma significance for voids of radius 15-20 Mpc/h. We also measure the void-galaxy cross-correlation at higher signal-to-noise and compare the inferred void bias with the autocorrelation results. Void bias is constant with scale for voids of a given size, but its value falls from 5.6 +/- 1.0 to below zero as the void radius increases from 15 to 30 Mpc/h. The comparison of our measurements with carefully matched galaxy mock catalogs, with no free parameters related to the voids, shows that model predictions can be reliably made for void correlations. We study the dependence of void bias on tracer density and void size with a view to future applications. In combination with our previous lensing measurements of void mass profiles, these clustering measurements provide another step towards using voids as cosmological tracers.