No Arabic abstract
Redshift space distortions (RSD) in the void-galaxy correlation $xi^s$ provide information on the linear growth rate of structure in low density environments. Accurate modelling of these RSD effects can also allow the use of voids in competitive Alcock-Paczynski measurements. Linear theory models of $xi^s$ are able to provide extremely good descriptions of simulation data on all scales provided the real space void positions are known. However, by reference to simulation data we demonstrate the failure of the assumptions implicit in current models of $xi^s$ for voids identified directly in redshift space, as would be simplest using real observational data. To overcome this problem we instead propose using a density-field reconstruction method based on the Zeldovich approximation to recover the real space void positions from redshift space data. We show that this recovers the excellent agreement between theory and data for $xi^s$. Performing the reconstruction requires an input cosmological model so, to be self-consistent, we have to perform reconstruction for every model to be tested. We apply this method to mock galaxy and void catalogues in the Big MultiDark $N$-body simulation and consistently recover the fiducial growth rate to a precision of $3.4%$ using the simulation volume of $(2.5;h^{-1}mathrm{Gpc})^3$.
We have derived estimators for the linear growth rate of density fluctuations using the cross-correlation function of voids and haloes in redshift space, both directly and in Fourier form. In linear theory, this cross-correlation contains only monopole and quadrupole terms. At scales greater than the void radius, linear theory is a good match to voids traced out by haloes in N-body simulations; small-scale random velocities are unimportant at these radii, only tending to cause small and often negligible elongation of the redshift-space cross-correlation function near its origin. By extracting the monopole and quadrupole from the cross-correlation function, we measure the linear growth rate without prior knowledge of the void profile or velocity dispersion. We recover the linear growth parameter $beta$ to 9% precision from an effective volume of 3(Gpc/h)^3 using voids with radius greater than 25Mpc/h. Smaller voids are predominantly sub-voids, which may be more sensitive to the random velocity dispersion; they introduce noise and do not help to improve the measurement. Adding velocity dispersion as a free parameter allows us to use information at radii as small as half of the void radius. The precision on $beta$ is reduced to approximately 5%. Contrary to the simple redshift-space distortion pattern in overdensities, voids show diverse shapes in redshift space, and can appear either elongated or flattened along the line of sight. This can be explained by the competing amplitudes of the local density contrast, plus the radial velocity profile and its gradient, with the latter two factors being determined by the cumulative density profile of voids. The distortion pattern is therefore determined solely by the void profile and is different for void-in-cloud and void-in-void. This diversity of redshift-space void morphology complicates measurements of the Alcock-Paczynski effect using voids.
We perform a comprehensive redshift-space distortion analysis based on cosmic voids in the large-scale distribution of galaxies observed with the Sloan Digital Sky Survey. To this end, we measure multipoles of the void-galaxy cross-correlation function and compare them with standard model predictions in cosmology. Merely considering linear-order theory allows us to accurately describe the data on the entire available range of scales and to probe void-centric distances down to about $2h^{-1}{rm Mpc}$. Common systematics, such as the Fingers-of-God effect, scale-dependent galaxy bias, and nonlinear clustering do not seem to play a significant role in our analysis. We constrain the growth rate of structure via the redshift-space distortion parameter $beta$ at two median redshifts, $beta(bar{z}=0.32)=0.599^{+0.134}_{-0.124}$ and $beta(bar{z}=0.54)=0.457^{+0.056}_{-0.054}$, with a precision that is competitive with state-of-the-art galaxy-clustering results. While the high-redshift constraint perfectly agrees with model expectations, we observe a mild $2sigma$ deviation at $bar{z}=0.32$, which increases to $3sigma$ when the data is restricted to the lowest available redshift range of $0.15<z<0.33$.
We outline how redshift-space distortions (RSD) can be measured from the angular correlation function w({theta}), of galaxies selected from photometric surveys. The natural degeneracy between RSD and galaxy bias can be minimized by comparing results from bins with top-hat galaxy selection in redshift, and bins based on the radial position of galaxy pair centres. This comparison can also be used to test the accuracy of the photometric redshifts. The presence of RSD will be clearly detectable with the next generation of photometric redshift surveys. We show that the Dark Energy Survey (DES) will be able to measure f(z){sigma}_8(z) to a 1{sigma} accuracy of (17 {times} b)%, using galaxies drawn from a single narrow redshift slice centered at z = 1. Here b is the linear bias, and f is the logarithmic rate of change of the linear growth rate with respect to the scale factor. Extending to measurements of w({theta}) for a series of bins of width 0.02(1 + z) over 0.5 < z < 1.4 will measure {gamma} to a 1{sigma} accuracy of 25%, given the model f = {Omega}_m(z)^{gamma}, and assuming a linear bias model that evolves such that b = 0.5 + z (and fixing other cosmological parameters). The accuracy of our analytic predictions is confirmed using mock catalogs drawn from simulations conducted by the MICE collaboration.
Euclid will survey galaxies in a cosmological volume of unprecedented size, providing observations of more than a billion objects distributed over a third of the full sky. Approximately 20 million of these galaxies will have spectroscopy available, allowing us to map the three-dimensional large-scale structure of the Universe in great detail. This paper investigates prospects for the detection of cosmic voids therein, and the unique benefit they provide for cosmology. In particular, we study the imprints of dynamic and geometric distortions of average void shapes and their constraining power on the growth of structure and cosmological distance ratios. To this end, we make use of the Flagship mock catalog, a state-of-the-art simulation of the data expected to be observed with Euclid. We arrange the data into four adjacent redshift bins, each of which contains about 11000 voids, and estimate the void-galaxy cross-correlation function in every bin. Fitting a linear-theory model to the data, we obtain constraints on $f/b$ and $D_M H$, where $f$ is the linear growth rate of density fluctuations, $b$ the galaxy bias, $D_M$ the comoving angular diameter distance, and $H$ the Hubble rate. In addition, we marginalize over two nuisance parameters included in our model to account for unknown systematic effects in the analysis. With this approach Euclid will be able to reach a relative precision of about 4% on measurements of $f/b$ and 0.5% on $D_M H$ in each redshift bin. Better modeling or calibration of the nuisance parameters may further increase this precision to 1% and 0.4%, respectively. Our results show that the exploitation of cosmic voids in Euclid will provide competitive constraints on cosmology even as a stand-alone probe. For example, the equation-of-state parameter $w$ for dark energy will be measured with a precision of about 10%, consistent with earlier more approximate forecasts.
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.