No Arabic abstract
The observed power spectrum in redshift space appears distorted due to the peculiar motion of galaxies, known as redshift-space distortions (RSD). While all the effects in RSD are accounted for by the simple mapping formula from real to redshift spaces, accurately modeling redshift-space power spectrum is rather difficult due to the non-perturbative properties of the mapping. Still, however, a perturbative treatment may be applied to the power spectrum at large-scales, and on top of a careful modeling of the Finger-of-God effect caused by the small-scale random motion, the redshift-space power spectrum can be expressed as a series of expansion which contains the higher-order correlations of density and velocity fields. In our previous work [JCAP 8 (Aug., 2016) 050], we provide a perturbation-theory inspired model for power spectrum in which the higher-order correlations are evaluated directly from the cosmological $N$-body simulations. Adopting a simple Gaussian ansatz for Finger-of-God effect, the model is shown to quantitatively describe the simulation results. Here, we further push this approach, and present an accurate power spectrum template which can be used to estimate the growth of structure as a key to probe gravity on cosmological scales. Based on the simulations, we first calibrate the uncertainties and systematics in the pertrubation theory calculation in a fiducial cosmological model. Then, using the scaling relations, the calibrated power spectrum template is applied to a different cosmological model. We demonstrate that with our new template, the best-fitted growth functions are shown to reproduce the fiducial values in a good accuracy of 1 % at $k<0.18 hompc$ for cosmologies with different Hubble parameters.
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 compute a general expression for the contribution of vector perturbations to the redshift-space distortion of galaxy surveys. We show that they contribute to the same multipoles of the correlation function as scalar perturbations and should thus in principle be taken into account in data analysis. We derive constraints for next-generation surveys on the amplitude of two sources of vector perturbations, namely non-linear clustering and topological defects. While topological defects leave a very small imprint on redshift-space distortions, we show that the multipoles of the correlation function are sensitive to vorticity induced by non-linear clustering. Therefore future redshift surveys such as DESI or the SKA should be capable of measuring such vector modes, especially with the hexadecapole which appears to be the most sensitive to the presence of vorticity.
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.
We use large volume N-body simulations to predict the clustering of dark matter in redshift space in f(R) modified gravity cosmologies. This is the first time that the nonlinear matter and velocity fields have been resolved to such a high level of accuracy over a broad range of scales in this class of models. We find significant deviations from the clustering signal in standard gravity, with an enhanced boost in power on large scales and stronger damping on small scales in the f(R) models compared to GR at redshifts z<1. We measure the velocity divergence (P_theta theta) and matter (P_delta delta) power spectra and find a large deviation in the ratios sqrt{P_theta theta/P_delta delta} and P_delta theta/P_deltadelta, between the f(R) models and GR for 0.03<k/(h/Mpc)<0.5. In linear theory these ratios equal the growth rate of structure on large scales. Our results show that the simulated ratios agree with the growth rate for each cosmology (which is scale dependent in the case of modified gravity) only for extremely large scales, k<0.06h/Mpc at z=0. The velocity power spectrum is substantially different in the f(R) models compared to GR, suggesting that this observable is a sensitive probe of modified gravity. We demonstrate how to extract the matter and velocity power spectra from the 2D redshift space power spectrum, P(k,mu), and can recover the nonlinear matter power spectrum to within a few percent for k<0.1h/Mpc. However, the model fails to describe the shape of the 2D power spectrum demonstrating that an improved model is necessary in order to reconstruct the velocity power spectrum accurately. The same model can match the monopole moment to within 3% for GR and 10% for the f(R) cosmology at k<0.2 h/Mpc at z=1. Our results suggest that the extraction of the velocity power spectrum from future galaxy surveys is a promising method to constrain deviations from GR.
We present the one-loop 2-point function of biased tracers in redshift space computed with Lagrangian perturbation theory, including a full resummation of both long-wavelength (infrared) displacements and associated velocities. The resulting model accurately predicts the power spectrum and correlation function of halos and mock galaxies from two different sets of N-body simulations at the percent level for quasi-linear scales, including the damping of the baryon acoustic oscillation signal due to the bulk motions of galaxies. We compare this full resummation with other, approximate, techniques including the moment expansion and Gaussian streaming model. We discuss infrared resummation in detail and compare our Lagrangian formulation with the Eulerian theory augmented by an infrared resummation based on splitting the input power spectrum into wiggle and no-wiggle components. We show that our model is able to recover unbiased cosmological parameters in mock data encompassing a volume much larger than what will be available to future galaxy surveys. We demonstrate how to efficiently compute the resulting expressions numerically, making available a fast Python code capable of rapidly computing these statistics in both configuration and Fourier space.