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Register a new userCosmological Information from the Small-scale Redshift Space Distortions
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The redshift-space distortion (RSD) in the observed distribution of galaxies is known as a powerful probe of cosmology. Observations of large-scale RSD have given tight constraints on the linear growth rate of the large-scale structures in the universe. On the other hand, the small-scale RSD, caused by galaxy random motions inside clusters, has not been much used in cosmology, but also has cosmological information because universes with different cosmological parameters have different halo mass functions and virialized velocities. We focus on the projected correlation function $w(r_p)$ and the multipole moments $xi_l$ on small scales ($1.4$ to $30 h^{-1}rm{Mpc}$). Using simulated galaxy samples generated from a physically motivated most bound particle (MBP)-galaxy correspondence scheme in the Multiverse Simulation, we examine the dependence of the small-scale RSD on the cosmological matter density parameter $Omega_m$, the satellite velocity bias with respect to MBPs, $b_v^s$, and the merger-time-scale parameter $alpha$. We find that $alpha=1.5$ gives an excellent fit to the $w(r_p)$ and $xi_l$ measured from the SDSS-KIAS value added galaxy catalog. We also define the ``strength of Fingers-of-God as the ratio of the parallel and perpendicular size of the contour in the two-point correlation function set by a specific threshold value and show that the strength parameter helps constraining $(Omega_m, b_v^s, alpha)$ by breaking the degeneracy among them. The resulting parameter values from all measurements are $(Omega_m,b_v^s)=(0.272pm0.013,0.982pm0.040)$, indicating a slight reduction of satellite galaxy velocity relative to the MBP. However, considering that the average MBP speed inside haloes is $0.94$ times the dark matter velocity dispersion, the main drivers behind the galaxy velocity bias are gravitational interactions, rather than baryonic effects.
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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 present improved modelling of the redshift-space distortions of galaxy clustering that arise from peculiar velocities. We create mock galaxy catalogues in the framework of the halo model, using data from the Bolshoi project. These mock galaxy populations are inserted into the haloes with additional degrees of freedom that govern spatial and kinematical biases of the galaxy populations relative to the dark matter. We explore this generalised halo model with an MCMC algorithm, comparing the predictions to data from the Galaxy And Mass Assembly (GAMA) survey, and thus derive one of the first constraints on the detailed kinematic degrees of freedom for satellite galaxies within haloes. With this approach, the distortions of the redshift-space galaxy autocorrelations can be accounted for down to spatial separations close to 10 kpc, opening the prospect of improved RSD measurements of the perturbation growth rate by the inclusion of data from nonlinear scales.
This is the second paper of a series where we study the clustering of LRG galaxies in the latest spectroscopic SDSS data release, DR6, which has 75000 LRG galaxies covering over 1 $Gpc^3/h^3$ for $0.15<z<0.47$. Here we focus on modeling redshift space distortions in $xisp$, the 2-point correlation in separate line-of-sight and perpendicular directions, at small scales and in the line-of-sight. We show that a simple Kaiser model for the anisotropic 2-point correlation function in redshift space, convolved with a distribution of random peculiar velocities with an exponential form, can describe well the correlation of LRG at all scales. We show that to describe with accuracy the so called fingers-of-God (FOG) elongations in the radial direction, it is necessary to model the scale dependence of both bias $b$ and the pairwise rms peculiar velocity $sigma_{12}$ with the distance. We show how both quantities can be inferred from the $xisp$ data. From $r simeq 10$ Mpc/h to $r simeq 1$ Mpc/h, both the bias and $sigma_{12}$ are shown to increase by a factor of two: from $b=2$ to $b=4$ and from $sigma_{12}=400$ to 800 Km/s. The later is in good agreement, within a 5 percent accuracy in the recovered velocities, with direct velocity measurements in dark matter simulations with $Omega_m=0.25$ and $sigma_8$=0.85.
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 propose a new analysis of small scale CMB data by introducing the cosmological dependency of the foreground signals, focusing first on the thermal Sunyaev-Zeldovich (tSZ) power spectrum, derived from the halo model. We analyse the latest observations by the South Pole Telescope (SPT) of the high-$ell$ power (cross) spectra at 90, 150 and 220 GHz, as the sum of CMB and tSZ signals, both depending on cosmological parameters, and remaining contaminants. In order to perform faster analyses, we propose a new tSZ modelling based on machine learning algorithms (namely Random Forest). We show that the additional information contained in the tSZ power spectrum tightens constraints on cosmological and tSZ scaling relation parameters. We combine for the first time the Planck tSZ data with SPT high-$ell$ to derive even stronger constraints. Finally, we show how the amplitude of the remaining kSZ power spectrum varies depending on the assumptions made on both tSZ and cosmological parameters.
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