A measurement of the Alcock-Paczynski effect using cosmic voids in the SDSS

We perform an Alcock-Paczynski test using stacked cosmic voids identified in the Sloan Digital Sky Survey (SDSS) Data Release 7 main sample and Data Release 10 LOWZ and CMASS samples. We find similar to 1500 voids out to redshift 0.6 using a heavily modified and extended version of the watershed algorithm ZOBOV, which we call VIDE (Void IDentification and Examination). To assess the impact of peculiar velocities, we use the mock void catalogues presented in Sutter et al. We find a constant uniform flattening of 14 per cent along the line of sight when peculiar velocities are included. This flattening appears universal for all void sizes at all redshifts and for all tracer densities. We also use these mocks to identify an optimal stacking strategy. After correcting for systematic effects, we find that our Alcock-Paczynski measurement leads to a preference of our best-fitting value of Omega(M) similar to 0.15 over Omega(M) = 1.0 by a likelihood ratio of 10. Likewise, we find a factor of 4.5 preference of the likelihood ratio for a Lambda cold dark matter Omega(M) = 0.3 model and a null measurement. Taken together, we find substantial evidence for the Alcock-Paczynski signal in our sample of cosmic voids. Our assessment using realistic mocks suggests that measurements with future SDSS releases and other surveys will provide tighter cosmological parameter constraints. The void-finding algorithm and catalogues used in this work will be made publicly available at http://www.cosmicvoids.net.