A measurement of the Alcock-Paczynski effect using cosmic voids in the SDSS
P. M. Sutter, Alice Pisani, Benjamin D. Wandelt, and David H. Weinberg

TL;DR
This paper measures the Alcock-Paczynski effect using cosmic voids in SDSS data, providing evidence for cosmological parameters and demonstrating the potential for future surveys to improve constraints.
Contribution
It introduces an extended void-finding algorithm, assesses systematic effects, and provides the first Alcock-Paczynski measurement using SDSS voids with mock validation.
Findings
Detected a 14% flattening along the line of sight due to peculiar velocities.
Preferred a matter density parameter of about 0.15 over 1.0.
Strongly favors a DM model with .3 over null results.
Abstract
We perform an Alcock-Paczynski test using stacked cosmic voids identified in the SDSS Data Release 7 main sample and Data Release 10 LOWZ and CMASS samples. We find ~1,500 voids out to redshift 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 catalogs presented in Sutter et al. (2013). We find a constant uniform flattening of 14% 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-fit value of over $\Omega_{\rm…
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