Cosmic voids in the large-scale structure of the Universe affect the peculiar motions of objects in their vicinity. Although these motions are difficult to observe directly, the clustering pattern of their surrounding tracers in redshift space is inf
luenced in a unique way. This allows to investigate the interplay between densities and velocities around voids, which is solely dictated by the laws of gravity. With the help of $N$-body simulations and derived mock-galaxy catalogs we calculate the average density fluctuations around voids identified with a watershed algorithm in redshift space and compare the results with the expectation from general relativity and the $Lambda$CDM model. We find linear theory to work remarkably well in describing the dynamics of voids. Adopting a Bayesian inference framework, we explore the full posterior of our model parameters and forecast the achievable accuracy on measurements of the growth rate of structure and the geometric distortion through the Alcock-Paczynski effect. Systematic errors in the latter are reduced from $sim15%$ to $sim5%$ when peculiar velocities are taken into account. The relative parameter uncertainties in galaxy surveys with number densities comparable to the SDSS MAIN (CMASS) sample probing a volume of $1h^{-3}{rm Gpc}^3$ yield $sigma_{f/b}left/(f/b)right.sim2%$ ($20%$) and $sigma_{D_AH}/D_AHsim0.2%$ ($2%$), respectively. At this level of precision the linear-theory model becomes systematics dominated, with parameter biases that fall beyond these values. Nevertheless, the presented method is highly model independent; its viability lies in the underlying assumption of statistical isotropy of the Universe.
How do peculiar velocities affect observed voids? To answer this question we use the VIDE toolkit to identify voids in mock galaxy populations embedded within an N-body simulation both with and without peculiar velocities included. We compare the res
ulting void populations to assess the impact on void properties. We find that void abundances and spherically-averaged radial density profiles are mildly affected by peculiar velocities. However, peculiar velocities can distort by up to 10% the shapes for a particular subset of voids depending on the void size and density contrast, which can lead to increased variance in Alcock-Paczynski test. We offer guidelines for performing optimal cuts on the void catalogue to reduce this variance by removing the most severely affected voids while preserving the unaffected ones. In addition, since this shape distortion is largely limited to the line of sight, we show that the void radii are only affected at the $sim$ 10% level and the macrocenter positions at the $sim$ 20% (even before performing cuts), meaning that cosmological probes based on the Integrated Sachs-Wolfe and gravitational lensing are not severely impacted by peculiar velocities.
We show that the number of observed voids in galaxy redshift surveys is a sensitive function of the equation of state of dark energy. Using the Fisher matrix formalism we find the error ellipses in the $w_0-w_a$ plane when the equation of state of da
rk energy is assumed to be of the form $w_{CPL}(z)=w_0 +w_a z/(1+z)$. We forecast the number of voids to be observed with the ESA Euclid satellite and the NASA WFIRST mission, taking into account updated details of the surveys to reach accurate estimates of their power. The theoretical model for the forecast of the number of voids is based on matches between abundances in simulations and the analytical prediction. To take into account the uncertainties within the model, we marginalize over its free parameters when calculating the Fisher matrices. The addition of the void abundance constraints to the data from Planck, HST and supernova survey data noticeably tighten the $w_0-w_a$ parameter space. We thus quantify the improvement in the constraints due to the use of voids and demonstrate that the void abundance is a sensitive new probe for the dark energy equation of state.
We present a general method for accelerating by more than an order of magnitude the convolution of pixelated functions on the sphere with a radially-symmetric kernel. Our method splits the kernel into a compact real-space component and a compact sphe
rical harmonic space component. These components can then be convolved in parallel using an inexpensive commodity GPU and a CPU. We provide models for the computational cost of both real-space and Fourier space convolutions and an estimate for the approximation error. Using these models we can determine the optimum split that minimizes the wall clock time for the convolution while satisfying the desired error bounds. We apply this technique to the problem of simulating a cosmic microwave background (CMB) anisotropy sky map at the resolution typical of the high resolution maps produced by the Planck mission. For the main Planck CMB science channels we achieve a speedup of over a factor of ten, assuming an acceptable fractional rms error of order 1.e-5 in the power spectrum of the output map.
We propose a novel technique to probe the expansion history of the Universe based on the clustering statistics of cosmic voids. In particular, we compute their two-point statistics in redshift space on the basis of realistic mock galaxy catalogs and
apply the Alcock-Paczynski test. In contrast to galaxies, we find void auto-correlations to be marginally affected by peculiar motions, providing a model-independent measure of cosmological parameters without systematics from redshift-space distortions. Because only galaxy-galaxy and void-galaxy correlations have been considered in these types of studies before, the presented method improves both statistical and systematic uncertainties on the product of angular diameter distance and Hubble rate, furnishing the potentially cleanest probe of cosmic geometry available to date.
We investigate the potential of using cosmic voids as a probe to constrain cosmological parameters through the gravitational lensing effect of the cosmic microwave background (CMB) and make predictions for the next generation surveys. By assuming the
detection of a series of $approx 5 - 10$ voids along a line of sight within a square-degree patch of the sky, we found that they can be used to break the degeneracy direction of some of the cosmological parameter constraints (for example $omega_b$ and $Omega_Lambda$) in comparison with the constraints from random CMB skies with the same size area for a survey with extensive integration time. This analysis is based on our current knowledge of the average void profile and analytical estimates of the void number function. We also provide combined cosmological parameter constraints between a sky patch where series of voids are detected and a patch without voids (a randomly selected patch). The full potential of this technique relies on an accurate determination of the void profile to $approx 10$% level. For a small-area CMB observation with extensive integration time and a high signal-to-noise ratio, CMB lensing with such series of voids will provide a complementary route to cosmological parameter constraints to the CMB observations. Example of parameter constraints with a series of five voids on a $1.0^{circ} times 1.0^{circ}$ patch of the sky are $100omega_b = 2.20 pm 0.27$, $omega_c = 0.120 pm 0.022$, $Omega_Lambda = 0.682 pm 0.078$, $Delta_{mathcal{R}}^2 = left(2.22 pm 7.79right) times 10^{-9}$, $n_s = 0.962 pm 0.097$ and $tau = 0.925 pm 1.747$ at 68% C.L.
We estimate the galaxy density along lines of sight to hard extragalactic gamma-ray sources by correlating source positions on the sky with a void catalog based on the Sloan Digital Sky Survey (SDSS). Extragalactic gamma-ray sources that are detected
at very high energy (VHE; E>100 GeV) or have been highlighted as VHE-emitting candidates in the Fermi Large Area Telescope hard source catalog (together referred to as VHE-like sources) are distributed along underdense lines of sight at the 2.4 sigma level. There is also a less suggestive correlation for the Fermi hard source population (1.7 sigma). A correlation between 10-500 GeV flux and underdense fraction along the line of sight for VHE-like and Fermi hard sources is found at 2.4 sigma and 2.6 sigma, respectively. The preference for underdense sight lines is not displayed by gamma-ray emitting galaxies within the second Fermi catalog, containing sources detected above 100 MeV, or the SDSS DR7 quasar catalog. We investigate whether this marginal correlation might be a result of lower extragalactic background light (EBL) photon density within the underdense regions and find that, even in the most extreme case of a entirely underdense sight line, the EBL photon density is only 2% less than the nominal EBL density. Translating this into gamma-ray attenuation along the line of sight for a highly attenuated source with opacity tau(E,z) ~5, we estimate that the attentuation of gamma-rays decreases no more than 10%. This decrease, although non-neglible, is unable to account for the apparent hard source correlation with underdense lines of sight.
We present VIDE, the Void IDentification and Examination toolkit, an open-source Python/C++ code for finding cosmic voids in galaxy redshift surveys and N-body simulations, characterizing their properties, and providing a platform for more detailed a
nalysis. At its core, VIDE uses a substantially enhanced version of ZOBOV (Neyinck 2008) to calculate a Voronoi tessellation for estimating the density field and a performing a watershed transform to construct voids. Additionally, VIDE provides significant functionality for both pre- and post-processing: for example, vide can work with volume- or magnitude-limited galaxy samples with arbitrary survey geometries, or dark matter particles or halo catalogs in a variety of common formats. It can also randomly subsample inputs and includes a Halo Occupation Distribution model for constructing mock galaxy populations. VIDE uses the watershed levels to place voids in a hierarchical tree, outputs a summary of void properties in plain ASCII, and provides a Python API to perform many analysis tasks, such as loading and manipulating void catalogs and particle members, filtering, plotting, computing clustering statistics, stacking, comparing catalogs, and fitting density profiles. While centered around ZOBOV, the toolkit is designed to be as modular as possible and accommodate other void finders. VIDE has been in development for several years and has already been used to produce a wealth of results, which we summarize in this work to highlight the capabilities of the toolkit. VIDE is publicly available at http://bitbucket.org/cosmicvoids/vide public and http://www.cosmicvoids.net.
Taking N-body simulations with volumes and particle densities tuned to match the SDSS DR7 spectroscopic main sample, we assess the ability of current void catalogs (e.g., Sutter et al. 2012b) to distinguish a model of coupled dark matter-dark energy
from {Lambda}CDM cosmology using properties of cosmic voids. Identifying voids with the VIDE toolkit, we find no statistically significant differences in the ellipticities, but find that coupling produces a population of significantly larger voids, possibly explaining the recent result of Tavasoli et al. (2013). In addition, we use the universal density profile of Hamaus et al. (2014) to quantify the relationship between coupling and density profile shape, finding that the coupling produces broader, shallower, undercompensated profiles for large voids by thinning the walls between adjacent medium-scale voids. We find that these differences are potentially measurable with existing void catalogs once effects from survey geometries and peculiar velocities are taken into account.
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 $0.6$ using a heavily modified and extended version of t
he 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 $Omega_{rm M}sim 0.15$ over $Omega_{rm M} = 1.0$ by a likelihood ratio of 10. Likewise, we find a factor of $4.5$ preference of the likelihood ratio for a $Lambda$CDM $Omega_{rm M} = 0.3$ 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 catalogs used in this work will be made publicly available at http://www.cosmicvoids.net.
