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We perform an Alcock-Paczynski test using stacked cosmic voids identified inthe SDSS Data Release 7 main sample and Data Release 10 LOWZ and CMASS samples.We find ~1,500 voids out to redshift $0.6$ using a heavily modified andextended version of the watershed algorithm ZOBOV, which we call VIDE (VoidIDentification and Examination). To assess the impact of peculiar velocities weuse the mock void catalogs presented in Sutter et al. (2013). We find aconstant uniform flattening of 14% along the line of sight when peculiarvelocities are included. This flattening appears universal for all void sizesat all redshifts and for all tracer densities. We also use these mocks toidentify an optimal stacking strategy. After correcting for systematic effectswe find that our Alcock-Paczynski measurement leads to a preference of ourbest-fit value of $\Omega_{\rm M}\sim 0.15$ over $\Omega_{\rm M} = 1.0$ by alikelihood ratio of 10. Likewise, we find a factor of $4.5$ preference of thelikelihood ratio for a $\Lambda$CDM $\Omega_{\rm M} = 0.3$ model and a nullmeasurement. Taken together, we find substantial evidence for theAlcock-Paczynski signal in our sample of cosmic voids. Our assessment usingrealistic mocks suggests that measurements with future SDSS releases and othersurveys will provide tighter cosmological parameter constraints. Thevoid-finding algorithm and catalogs used in this work will be made publiclyavailable at http://www.cosmicvoids.net.

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