3,585 research outputs found

    Measuring the hydrostatic mass bias in galaxy clusters by combining Sunyaev-Zel'dovich and CMB lensing data

    Full text link
    The cosmological parameters prefered by the cosmic microwave background (CMB) primary anisotropies predict many more galaxy clusters than those that have been detected via the thermal Sunyaev-Zeldovich (tSZ) effect. This tension has attracted considerable attention since it could be evidence of physics beyond the simplest Λ\LambdaCDM model. However, an accurate and robust calibration of the mass-observable relation for clusters is necessary for the comparison, which has been proven difficult to obtain so far. Here, we present new contraints on the mass-pressure relation by combining tSZ and CMB lensing measurements about optically-selected clusters. Consequently, our galaxy cluster sample is independent from the data employed to derive cosmological constrains. We estimate an average hydrostatic mass bias of b=0.26±0.07b = 0.26 \pm 0.07, with no significant mass nor redshift evolution. This value greatly reduces the tension between the predictions of Λ\LambdaCDM and the observed abundance of tSZ clusters while being in agreement with recent estimations from tSZ clustering. On the other hand, our value for bb is higher than the predictions from hydro-dynamical simulations. This suggests the existence of mechanisms driving large departures from hydrostatic equilibrium and that are not included in state-of-the-art simulations, and/or unaccounted systematic errors such as biases in the cluster catalogue due to the optical selection.Comment: 4 pages, 3 figure

    Status of superpressure balloon technology in the United States

    Get PDF
    Superpressure mylar balloon technology in United States - applications, balloon size criteria, and possible improvement

    Extending the halo mass resolution of NN-body simulations

    Full text link
    We present a scheme to extend the halo mass resolution of N-body simulations of the hierarchical clustering of dark matter. The method uses the density field of the simulation to predict the number of sub-resolution dark matter haloes expected in different regions. The technique requires as input the abundance of haloes of a given mass and their average clustering, as expressed through the linear and higher order bias factors. These quantities can be computed analytically or, more accurately, derived from a higher resolution simulation as done here. Our method can recover the abundance and clustering in real- and redshift-space of haloes with mass below ∼7.5×1013h−1M⊙\sim 7.5 \times 10^{13}h^{-1}M_{\odot} at z=0z=0 to better than 10%. We demonstrate the technique by applying it to an ensemble of 50 low resolution, large-volume NN-body simulations to compute the correlation function and covariance matrix of luminous red galaxies (LRGs). The limited resolution of the original simulations results in them resolving just two thirds of the LRG population. We extend the resolution of the simulations by a factor of 30 in halo mass in order to recover all LRGs. With existing simulations it is possible to generate a halo catalogue equivalent to that which would be obtained from a NN-body simulation using more than 20 trillion particles; a direct simulation of this size is likely to remain unachievable for many years. Using our method it is now feasible to build the large numbers of high-resolution large volume mock galaxy catalogues required to compute the covariance matrices necessary to analyse upcoming galaxy surveys designed to probe dark energy.Comment: 11 pages, 7 Figure
    • …
    corecore