No Arabic abstract
We develop a maximum likelihood based method of reconstructing band powers of the density and velocity power spectra at each wavenumber bins from the measured clustering features of galaxies in redshift space, including marginalization over uncertainties inherent in the Fingers-of-God (FoG) effect. The reconstruction can be done assuming that the density and velocity power spectra depend on the redshift-space power spectrum having different angular modulations of mu with mu^{2n} (n=0,1,2) and that the model FoG effect is given as a multiplicative function in the redshift-space spectrum. By using N-body simulations and the halo catalogs, we test our method by comparing the reconstructed power spectra with the simulations. For the spectrum of mu^0 or equivalently the density power spectrum P_dd(k), our method recovers the amplitudes to a few percent accuracies up to k=0.3 h/Mpc for both dark matter and halos. For the power spectrum of mu^2, which is equivalent to the density-velocity spectrum P_dv(k) in the linear regime, our method can recover the input power spectrum for dark matter up to k=0.2 h/Mpc and at both z=0 and 1, if using the adequate FoG model. However, for the halo spectrum, the reconstructed spectrum shows greater amplitudes than the simulation P_dv(k). We argue that the disagreement is ascribed to nonlinearity effect that arises from the cross-bispectra of density and velocity perturbations. Using the perturbation theory, we derive the nonlinear correction term, and find that the leading-order correction term is proportional to mu^2 and increases the mu^2-power spectrum amplitudes at larger k, at lower redshifts and for more massive halos. We find that adding the nonlinearity correction term to the simulation P_dv(k) can fairly well reproduce the reconstructed P_dv(k) for halos up to k~0.2 h/Mpc.
Redshift-space distortions (RSD) generically affect any spatially-dependent observable that is mapped using redshift information. The effect on the observed clustering of galaxies is the primary example of this. This paper is devoted to another example: the effect of RSD on the apparent peculiar motions of tracers as inferred from their positions in redshift space (i.e. the observed distance). Our theoretical study is motivated by practical considerations, mainly, the direct estimation of the velocity power spectrum, which is preferably carried out using the tracers redshift-space position (so as to avoid uncertainties in distance measurements). We formulate the redshift-space velocity field and show that RSD enters as a higher-order effect. Physically, this effect may be interpreted as a dissipative correction to the usual perfect-fluid description of dark matter. We show that the effect on the power spectrum is a damping on relatively large, quasilinear scales ($k>0.01,h,{rm Mpc}^{-1}$), as was observed, though unexplained, in $N$-body simulations elsewhere. This paper presents two power spectrum models for the the peculiar velocity field in redshift space, both of which can be considered velocity analogues of existing clustering models. In particular, we show that the Finger-of-God effect, while also present in the velocity field, cannot be entirely blamed for the observed damping in simulations. Our work provides some of the missing modelling ingredients required for a density--velocity multi-tracer analysis, which has been proposed for upcoming redshift surveys.
Aims. Using the VIMOS Public Extragalactic Redshift Survey (VIPERS) we aim to jointly estimate the key parameters that describe the galaxy density field and its spatial correlations in redshift space. Methods. We use the Bayesian formalism to jointly reconstruct the redshift-space galaxy density field, power spectrum, galaxy bias and galaxy luminosity function given the observations and survey selection function. The high-dimensional posterior distribution is explored using the Wiener filter within a Gibbs sampler. We validate the analysis using simulated catalogues and apply it to VIPERS data taking into consideration the inhomogeneous selection function. Results. We present joint constraints on the anisotropic power spectrum as well as the bias and number density of red and blue galaxy classes in luminosity and redshift bins as well as the measurement covariances of these quantities. We find that the inferred galaxy bias and number density parameters are strongly correlated although these are only weakly correlated with the galaxy power spectrum. The power spectrum and redshift-space distortion parameters are in agreement with previous VIPERS results with the value of the growth rate $fsigma_8 = 0.38$ with 18% uncertainty at redshift 0.7.
I propose to compare the redshift-space density field directly to the REAL-SPACE velocity field. Such a comparison possesses all of the advantages of the conventional redshift-space analyses, while at the same time it is free of their disadvantages. In particular, the model-dependent reconstruction of the density field in real space is unnecessary, and so is the reconstruction of the velocity field in redshift space. The redshift-space velocity field can be reconstructed only at the linear order, because only at this order it is irrotational. Unlike the conventional redshift-space density--velocity comparisons, the comparison proposed here does not have to be restricted to the linear regime. Nonlinear effects can then be used to break the Omega-bias degeneracy plaguing the analyses based on the linear theory. I present a degeneracy-breaking method for the case of nonlinear but local bias.
We investigate a potential of the higher multipole power spectra of the galaxy distribution in redshift space as a cosmological probe on halo scales. Based on the fact that a halo model explains well the multipole power spectra of the luminous red galaxy (LRG) sample in the Sloan Digital Sky Survey (SDSS), we focus our investigation on the random motions of the satellite LRGs that determine the higher multipole spectra at large wavenumbers. We show that our theoretical model fits the higher multipole spectra at large wave numbers from N-body numerical simulations and we apply these results for testing the gravity theory and the velocity structure of galaxies on the halo scales. In this analysis, we use the multipole spectra P_4(k) and P_6(k) on the small scales of the range of wavenumber 0.3<k/[h{Mpc}^{-1}]<0.6, which is in contrast to the usual method of testing gravity by targeting the linear growth rate on very large scales. We demonstrate that our method could be useful for testing gravity on the halo scales.
Upcoming galaxy redshift surveys promise to significantly improve current limits on primordial non-Gaussianity (PNG) through measurements of 2- and 3-point correlation functions in Fourier space. However, realizing the full potential of this dataset is contingent upon having both accurate theoretical models and optimized analysis methods. Focusing on the local model of PNG, parameterized by $f_{rm NL}$, we perform a Monte-Carlo Markov Chain analysis to confront perturbation theory predictions of the halo power spectrum and bispectrum in real space against a suite of N-body simulations. We model the halo bispectrum at tree-level, including all contributions linear and quadratic in $f_{rm NL}$, and the halo power spectrum at 1-loop, including tree-level terms up to quadratic order in $f_{rm NL}$ and all loops induced by local PNG linear in $f_{rm NL}$. Keeping the cosmological parameters fixed, we examine the effect of informative priors on the linear non-Gaussian bias parameter on the statistical inference of $f_{rm NL}$. A conservative analysisof the combined power spectrum and bispectrum, in which only loose priors are imposed and all parameters are marginalized over, can improve the constraint on $f_{rm NL}$ by more than a factor of 5 relative to the power spectrum-only measurement. Imposing a strong prior on $b_phi$, or assuming bias relations for both $b_phi$ and $b_{phidelta}$ (motivated by a universal mass function assumption), improves the constraints further by a factor of few. In this case, however, we find a significant systematic shift in the inferred value of $f_{rm NL}$ if the same range of wavenumber is used. Likewise, a Poisson noise assumption can lead to significant systematics, and it is thus essential to leave all the stochastic amplitudes free.