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.
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 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.
We present and study cosmic voids identified using the watershed void finder VIDE in the Sloan Digital Sky Survey Data Release 9, compare these voids to ones identified in mock catalogs, and assess the impact of the survey mask on void statistics suc
h as number functions, ellipticity distributions, and radial density profiles. The nearly 1,000 identified voids span three nearly volume-limited samples from redshift z = 0.43 to 0.7. For comparison we use 98 of the publicly available 2LPT-based mock galaxy catalogs of Manera et al., and also generate our own mock catalogs by applying a Halo Occupation Distribution model to an N-body simulation. We find that the mask reduces the number density of voids at all scales by a factor of three and slightly skews the relative size distributions. This engenders an increase in the mean ellipticity by roughly 30%. However, we find that radial density profiles are largely robust to the effects of the mask. We see excellent agreement between the data and both mock catalogs, and find no tension between the observed void properties and the properties derived from {Lambda}CDM simulations. We have added the void catalogs from both data and mock galaxy populations discussed in this work to the Public Cosmic Void Catalog at http://www.cosmicvoids.net.
To study the impact of sparsity and galaxy bias on void statistics, we use a single large-volume, high-resolution N-body simulation to compare voids in multiple levels of subsampled dark matter, halo populations, and mock galaxies from a Halo Occupat
ion Distribution model tuned to different galaxy survey densities. We focus our comparison on three key observational statistics: number functions, ellipticity distributions, and radial density profiles. We use the hierarchical tree structure of voids to interpret the impacts of sampling density and galaxy bias, and theoretical and empirical functions to describe the statistics in all our sample populations. We are able to make simple adjustments to theoretical expectations to offer prescriptions for translating from analytics to the void properties measured in realistic observations. We find that sampling density has a much larger effect on void sizes than galaxy bias. At lower tracer density, small voids disappear and the remaining voids are larger, more spherical, and have slightly steeper profiles. When a proper lower mass threshold is chosen, voids in halo distributions largely mimic those found in galaxy populations, except for ellipticities, where galaxy bias leads to higher values. We use the void density profile of Hamaus et al. (2014) to show that voids follow a self-similar and universal trend, allowing simple translations between voids studied in dark matter and voids identified in galaxy surveys. We have added the mock void catalogs used in this work to the Public Cosmic Void Catalog at http://www.cosmicvoids.net.
Peculiar velocities in the nearby Universe can be measured via the kinetic Sunyaev-Zeldovich (kSZ) effect. Using a statistical method based on an optimised cross-correlation with nearby galaxies, we extract the kSZ signal generated by plasma halo of
galaxies from the Cosmic Microwave Background (CMB) temperature anisotropies observed by the Wilkinson Microwave Anisotropy Probe (WMAP). Marginalising over the thermal Sunyaev-Zeldovich contribution from clusters of galaxies, possible unresolved point source contamination, and Galactic foregrounds (dust, synchrotron and free-free emission), we report a kSZ bulk flow signal present at the 90% confidence level in the seven-year WMAP data. When only galaxies within 50 Mpc/h are included in the kSZ template we find a bulk flow in the CMB frame of |V|=533 +/- 263 km/s, in the direction l=324 +/- 27, b=-7 +/- 17, consistent with bulk flow measurements on a similar scale using classical distance indicators. We show how this comparison constrains the (ionised) baryonic budget in the local universe. On very large (~ 500 Mpc/h) scales, we find a 95% upper limit of 470 km/s, inconsistent with some analyses of bulk flow of clusters from the kSZ. We estimate that the significance of the bulk flow signal may increase to 3-5 sigma using data from the PLANCK probe.
We present a purely geometrical method for probing the expansion history of the Universe from the observation of the shape of stacked voids in spectroscopic redshift surveys. Our method is an Alcock-Paczynski (AP) test based on the average sphericity
of voids posited on the local isotropy of the Universe. It works by comparing the temporal extent of cosmic voids along the line of sight with their angular, spatial extent. We describe the algorithm that we use to detect and stack voids in redshift shells on the light cone and test it on mock light cones produced from N-body simulations. We establish a robust statistical model for estimating the average stretching of voids in redshift space and quantify the contamination by peculiar velocities. Finally, assuming that the void statistics that we derive from N-body simulations is preserved when considering galaxy surveys, we assess the capability of this approach to constrain dark energy parameters. We report this assessment in terms of the figure of merit (FoM) of the dark energy task force and in particular of the proposed EUCLID mission which is particularly suited for this technique since it is a spectroscopic survey. The FoM due to stacked voids from the EUCLID wide survey may double that of all other dark energy probes derived from EUCLID data alone (combined with Planck priors). In particular, voids seem to outperform Baryon Acoustic Oscillations by an order of magnitude. This result is consistent with simple estimates based on mode-counting. The AP test based on stacked voids may be a significant addition to the portfolio of major dark energy probes and its potentialities must be studied in detail.
Peculiar velocities arise from gravitational instability, and thus are linked to the surrounding distribution of matter. In order to understand the motion of the Local Group with respect to the Cosmic Microwave Background, a deep all-sky map of the g
alaxy distribution is required. Here we present a new redshift compilation of 69~160 galaxies, dubbed 2M++, to map large-scale structures of the Local Universe over nearly the whole sky, and reaching depths of K <= 12.5, or 200 Mpc/h. The target catalogue is based on the Two-Micron-All-Sky Extended Source Catalog (2MASS-XSC). The primary sources of redshifts are the 2MASS Redshift Survey, the 6dF galaxy redshift survey and the Sloan Digital Sky Survey (DR7). We assess redshift completeness in each region and compute the weights required to correct for redshift incompleteness and apparent magnitude limits, and discuss corrections for incompleteness in the Zone of Avoidance. We present the density field for this survey, and discuss the importance of large-scale structures such as the Shapley Concentration.
We describe a accurate and fast pixel-based statistical method to interpolate fields of arbitrary spin on the sphere. We call this method Fast and Lean Interpolation on the Sphere (FLINTS). The method predicts the optimal interpolated values based on
the theory of isotropic Gaussian random fields and provides an accurate error estimate at no additional cost. We use this method to compute lensed Cosmic Microwave Background (CMB) maps precisely and quickly, achieving a relative precision of 0.02% at a HEALPix resolution of Nside=4096, for a bandlimit of l_max=4096 in the same time it takes to simulate the original, unlensed CMB map. The method is suitable for efficient, distributed memory parallelization. The power spectra of our lensed maps are accurate to better than 0.5% at l=3000 for the temperature, the E and B mode of the polarization. As expected theoretically, we demonstrate that, on realistic cases, this method is between two to three orders of magnitude more precise than other known interpolation methods for the same computational cost.
We use the formalism of constrained Gaussian random field to compute a precise large scale simulation of the 60 Mpc/h volume of our Local Universe. We derive the constraints from the reconstructed peculiar velocities of the 2MASS Redshift Survey. We
obtain a correlation of 0.97 between the log-density field of the dark matter distribution of the simulation and the log-density of observed galaxies of the Local Universe. We achieve a good comparison of the simulated velocity field to the observed velocity field obtained from the galaxy distances of the NBG-3k. At the end, we compare the two-point correlation function of both the 2MRS galaxies and of the dark matter particles of the simulation. We conclude that this method is a very promising technique of exploring the dynamics and the particularities the Universe in our neighbourhood.
