Cluster versus POTENT Density and Velocity Fields: Cluster Biasing and Omega

The density and velocity fields as extracted from the Abell/ACO clusters are compared to the corresponding fields recovered by the POTENT method from the Mark~III peculiar velocities of galaxies. In order to minimize non-linear effects and to deal with ill-sampled regions we smooth both fields using a Gaussian window with radii ranging between 12 - 20\hmpc. The density and velocity fields within 70\hmpc exhibit similarities, qualitatively consistent with gravitational instability theory and a linear biasing relation between clusters and mass. The random and systematic errors are evaluated with the help of mock catalogs. Quantitative comparisons within a volume containing $\sim\!12$ independent samples yield \betac\equiv\Omega^{0.6}/b_c=0.22\pm0.08, where $b_c$ is the cluster biasing parameter at 15\hmpc. If $b_c \sim 4.5$, as indicated by the cluster correlation function, our result is consistent with $\Omega \sim 1$.Comment: 18 pages, latex, 2 ps figures 6 gif figures. Accepted for pubblications in MNRA

Nonlinear Peculiar-Velocity Analysis and PCA

We allow for nonlinear effects in the likelihood analysis of peculiar velocities, and obtain ~35%-lower values for the cosmological density parameter and for the amplitude of mass-density fluctuations. The power spectrum in the linear regime is assumed to be of the flat LCDM model (h=0.65, n=1) with only Om_m free. Since the likelihood is driven by the nonlinear regime, we "break" the power spectrum at k_b=0.2 h/Mpc and fit a two-parameter power-law at k>k_b. This allows for an unbiased fit in the linear regime. Tests using improved mock catalogs demonstrate a reduced bias and a better fit. We find for the Mark III and SFI data Om_m=0.35+-0.09$ with sigma_8*Om_m^0.6=0.55+-0.10 (90% errors). When allowing deviations from \lcdm, we find an indication for a wiggle in the power spectrum in the form of an excess near k~0.05 and a deficiency at k~0.1 h/Mpc --- a "cold flow" which may be related to a feature indicated from redshift surveys and the second peak in the CMB anisotropy. A chi^2 test applied to principal modes demonstrates that the nonlinear procedure improves the goodness of fit. The Principal Component Analysis (PCA) helps identifying spatial features of the data and fine-tuning the theoretical and error models. We address the potential for optimal data compression using PCA.Comment: 15 pages, LaTex, in Mining the Sky, July 31 - August 4, 2000, Garching, German

The impact of assembly bias on the halo occupation in hydrodynamical simulations

We investigate the variations in galaxy occupancy of the dark matter haloes with the large-scale environment and halo formation time, using two state-of-the-art hydrodynamical cosmological simulations, EAGLE and Illustris. For both simulations, we use three galaxy samples with a fixed number density ranked by stellar mass. For these samples, we find that low-mass haloes in the most dense environments are more likely to host a central galaxy than those in the least dense environments. When splitting the halo population by formation time, these relations are stronger. Hence, at a fixed low halo mass, early-formed haloes are more likely to host a central galaxy than late-formed haloes since they have had more time to assemble. The satellite occupation shows a reverse trend where early-formed haloes host fewer satellites due to having more time to merge with the central galaxy. We also analyse the stellar mass–halo mass relation for central galaxies in terms of the large-scale environment and formation time of the haloes. We find that low-mass haloes in the most dense environment host relatively more massive central galaxies. This trend is also found when splitting the halo population by age, with early-formed haloes hosting more massive galaxies. Our results are in agreement with previous findings from semi-analytical models, providing robust predictions for the occupancy variation signature in the halo occupation distribution of galaxy formation models

Cosmological Parameters from Velocities, CMB and Supernovae

We compare and combine likelihood functions of the cosmological parameters Omega_m, h and sigma_8, from peculiar velocities, CMB and type Ia supernovae. These three data sets directly probe the mass in the Universe, without the need to relate the galaxy distribution to the underlying mass via a "biasing" relation. We include the recent results from the CMB experiments BOOMERANG and MAXIMA-1. Our analysis assumes a flat Lambda CDM cosmology with a scale-invariant adiabatic initial power spectrum and baryonic fraction as inferred from big-bang nucleosynthesis. We find that all three data sets agree well, overlapping significantly at the 2 sigma level. This therefore justifies a joint analysis, in which we find a joint best fit point and 95 per cent confidence limits of Omega_m=0.28 (0.17,0.39), h=0.74 (0.64,0.86), and sigma_8=1.17 (0.98,1.37). In terms of the natural parameter combinations for these data sigma_8 Omega_m^0.6 = 0.54 (0.40,0.73), Omega_m h = 0.21 (0.16,0.27). Also for the best fit point, Q_rms-ps = 19.7 muK and the age of the universe is 13.2 Gyr.Comment: 8 pages, 5 figures. Submitted to MNRA

Cosmological Density and Power Spectrum from Peculiar Velocities: Nonlinear Corrections and PCA

We allow for nonlinear effects in the likelihood analysis of galaxy peculiar velocities, and obtain ~35%-lower values for the cosmological density parameter Om and the amplitude of mass-density fluctuations. The power spectrum in the linear regime is assumed to be a flat LCDM model (h=0.65, n=1, COBE) with only Om as a free parameter. Since the likelihood is driven by the nonlinear regime, we "break" the power spectrum at k_b=0.2 h/Mpc and fit a power law at k>k_b. This allows for independent matching of the nonlinear behavior and an unbiased fit in the linear regime. The analysis assumes Gaussian fluctuations and errors, and a linear relation between velocity and density. Tests using proper mock catalogs demonstrate a reduced bias and a better fit. We find for the Mark3 and SFI data Om_m=0.32+-0.06 and 0.37+-0.09 respectively, with sigma_8*Om^0.6 = 0.49+-0.06 and 0.63+-0.08, in agreement with constraints from other data. The quoted 90% errors include cosmic variance. The improvement in likelihood due to the nonlinear correction is very significant for Mark3 and moderately so for SFI. When allowing deviations from LCDM, we find an indication for a wiggle in the power spectrum: an excess near k=0.05 and a deficiency at k=0.1 (cold flow). This may be related to the wiggle seen in the power spectrum from redshift surveys and the second peak in the CMB anisotropy. A chi^2 test applied to modes of a Principal Component Analysis (PCA) shows that the nonlinear procedure improves the goodness of fit and reduces a spatial gradient of concern in the linear analysis. The PCA allows addressing spatial features of the data and fine-tuning the theoretical and error models. It shows that the models used are appropriate for the cosmological parameter estimation performed. We address the potential for optimal data compression using PCA.Comment: 18 pages, LaTex, uses emulateapj.sty, ApJ in press (August 10, 2001), improvements to text and figures, updated reference

Gravitational Collapse with a Cosmological Constant

We consider the effect of a positive cosmological constant on spherical gravitational collapse to a black hole for a few simple, analytic cases. We construct the complete Oppenheimer-Snyder-deSitter (OSdS) spacetime, the generalization of the Oppenheimer-Snyder solution for collapse from rest of a homogeneous dust ball in an exterior vacuum. In OSdS collapse, the cosmological constant may affect the onset of collapse and decelerate the implosion initially, but it plays a diminishing role as the collapse proceeds. We also construct spacetimes in which a collapsing dust ball can bounce, or hover in unstable equilibrium, due to the repulsive force of the cosmological constant. We explore the causal structure of the different spacetimes and identify any cosmological and black hole event horizons which may be present.Comment: 7 pages, 10 figures; To appear in Phys. Rev.