Goodness-of-Fit Analysis of Radial Velocities Surveys

Using eigenmode expansion of the Mark-3 and SFI surveys of cosmological radial velocities a goodness-of-fit analysis is applied on a mode-by-mode basis. This differential analysis complements theBayesian maximum likelihood analysis that finds the most probable model given the data. Analyzing the surveys with their corresponding most likely models from the CMB-like family of models, as well as with the currently popular Lambda-CDM model, reveals a systematic inconsistency of the data with these `best' models. There is a systematic trend of the cumulative chi^2 to increase with the mode number (where the modes are sorted by decreasing order of the eigenvalues). This corresponds to a decrease of the chi^2 with the variance associated with a mode, and hence with its effective scale. It follows that the differential analysis finds that on small (large) scales the global analysis of all the modes `puts' less (more) power than actually required by the data. This observed trend might indicate one of the followings: a. The theoretical model (i.e. power spectrum) or the error model (or both) have an excess of power on large scales; b. Velocity bias; c. The velocity data suffers from still uncorrected systematic errors.Comment: 12 pages including 2 figures. Accepted for publication in the Ap.J. Letter

Cold Flows and Large Scale Tides

Several studies have indicated that the local cosmic velocity field is rather cold, in particular in the regions outside the massive, virialized clusters of galaxies. If our local cosmic environment is taken to be a representative volume of the Universe, the repercussion of this finding is that either we live in a low-$\Omega$ Universe and/or that the galaxy distribution is a biased reflection of the underlying mass distribution. Otherwise, the pronounced nature of the observed galaxy distribution would be irreconcilable with the relatively quiet flow of the galaxies. Here we propose a different view on this cosmic dilemma, stressing the fact that our cosmic neighbourhood embodies a region of rather particular dynamical properties, and henceforth we are apt to infer flawed conclusions with respect to the global Universe. Suspended between two huge mass concentrations, the Great Attractor region and the Perseus-Pisces chain, we find ourselves in a region of relatively low density yet with a very strong tidal shear. This tidal field induces a local velocity field with a significant large-scale bulk flow but a low small-scale velocity dispersion. By means of constrained realizations of our local Universe, consisting of Wiener-filtered reconstructions inferred from the Mark III catalogue of galaxy peculiar velocities in combination with appropriate spectrally determined fluctuations, we study the implications for our local velocity field. We find that we live near a local peak in the distribution of the cosmic Mach number, $|v_{bulk}|/\sigma_v$, and that our local cosmic niche is located in the tail of the Mach number distribution function.Comment: Contribution to `Evolution of Large Scale Structure', MPA/ESO Conference, August 1997, eds. A. Banday & R. Sheth, Twin Press. 5 pages of LaTeX including 3 postscript figures. Uses tp.sty and psfi

Weighing the Local Group in the Presence of Dark Energy

We revise the mass estimate of the Local Group (LG) when Dark Energy (in the form of the Cosmological Constant) is incorporated into the Timing Argument (TA) mass estimator for the Local Group (LG). Assuming the age of the Universe and the Cosmological Constant according to the recent values from the Planck CMB experiment, we find the mass of the LG to be M_TAL = (4.73 +- 1.03) x 10^{12} M_sun, which is 13% higher than the classical TA mass estimate. This partly explains the discrepancy between earlier results from LCDM simulations and the classical TA. When a similar analysis is performed on 16 LG-like galaxy pairs from the CLUES simulations, we find that the scatter in the ratio of the virial to the TA estimated mass is given by M_vir/M_TAL = 1.04 +-0.16. Applying it to the LG mass estimation we find a calibrated M_vir = (4.92 +- 1.08 (obs) +- 0.79 (sys)) x 10^{12} M_sun.Comment: 5 pages, 5 figures, Accepted for publication in MNRAS (Letters