3,926 research outputs found

    How closely do baryons follow dark matter on large scales?

    Full text link
    We investigate the large-scale clustering and gravitational interaction of baryons and dark matter (DM) over cosmic time using a set of collisionless N-body simulations. Both components, baryons and DM, are evolved from distinct primordial density and velocity power spectra as predicted by early-universe physics. We first demonstrate that such two-component simulations require an unconventional match between force and mass resolution (i.e. force softening on at least the mean particle separation scale). Otherwise, the growth on any scale is not correctly recovered because of a spurious coupling between the two species at the smallest scales. With these simulations, we then demonstrate how the primordial differences in the clustering of baryons and DM are progressively diminished over time. In particular, we explicitly show how the BAO signature is damped in the spatial distribution of baryons and imprinted in that of DM. This is a rapid process, yet it is still not fully completed at low redshifts. On large scales, the overall shape of the correlation function of baryons and DM differs by 2% at z = 9 and by 0.2% at z = 0. The differences in the amplitude of the BAO peak are approximately a factor of 5 larger: 10% at z = 9 and 1% at z = 0. These discrepancies are, however, smaller than effects expected to be introduced by galaxy formation physics in both the shape of the power spectrum and in the BAO peak, and are thus unlikely to be detected given the precision of the next generation of galaxy surveys. Hence, our results validate the standard practice of modelling the observed galaxy distribution using predictions for the total mass clustering in the Universe.Comment: 9 pages, 6 figures. Replaced with version published in MNRA

    Adaptive scanning - a proposal how to scan theoretical predictions over a multi-dimensional parameter space efficiently

    Full text link
    A method is presented to exploit adaptive integration algorithms using importance sampling, like VEGAS, for the task of scanning theoretical predictions depending on a multi-dimensional parameter space. Usually, a parameter scan is performed with emphasis on certain features of a theoretical prediction. Adaptive integration algorithms are well-suited to perform this task very efficiently. Predictions which depend on parameter spaces with many dimensions call for such an adaptive scanning algorithm.Comment: 8 pages, 4 figure

    Halo assembly bias and the tidal anisotropy of the local halo environment

    Full text link
    We study the role of the local tidal environment in determining the assembly bias of dark matter haloes. Previous results suggest that the anisotropy of a halo's environment (i.e, whether it lies in a filament or in a more isotropic region) can play a significant role in determining the eventual mass and age of the halo. We statistically isolate this effect using correlations between the large-scale and small-scale environments of simulated haloes at z=0z=0 with masses between 1011.6(m/h1M)1014.910^{11.6}\lesssim (m/h^{-1}M_{\odot})\lesssim10^{14.9}. We probe the large-scale environment using a novel halo-by-halo estimator of linear bias. For the small-scale environment, we identify a variable αR\alpha_R that captures the tidal anisotropy\textit{tidal anisotropy} in a region of radius R=4R200bR=4R_{\textrm{200b}} around the halo and correlates strongly with halo bias at fixed mass. Segregating haloes by αR\alpha_R reveals two distinct populations. Haloes in highly isotropic local environments (αR0.2\alpha_R\lesssim0.2) behave as expected from the simplest, spherically averaged analytical models of structure formation, showing a negative\textit{negative} correlation between their concentration and large-scale bias at all\textit{all} masses. In contrast, haloes in anisotropic, filament-like environments (αR0.5\alpha_R\gtrsim0.5) tend to show a positive\textit{positive} correlation between bias and concentration at any mass. Our multi-scale analysis cleanly demonstrates how the overall assembly bias trend across halo mass emerges as an average over these different halo populations, and provides valuable insights towards building analytical models that correctly incorporate assembly bias. We also discuss potential implications for the nature and detectability of galaxy assembly bias.Comment: 19 pages, 15 figures; v2: revised in response to referee comments, added references and discussion, conclusions unchanged. Accepted in MNRA

    Properties of Dark Matter Haloes in Clusters, Filaments, Sheets and Voids

    Get PDF
    Using a series of high-resolution N-body simulations of the concordance cosmology we investigate how the formation histories, shapes and angular momenta of dark-matter haloes depend on environment. We first present a classification scheme that allows to distinguish between haloes in clusters, filaments, sheets and voids in the large-scale distribution of matter. This method is based on a local-stability criterion for the orbits of test particles and closely relates to the Zel'dovich approximation. Applying this scheme to our simulations we then find that: i) Mass assembly histories and formation redshifts strongly depend on environment for haloes of mass M<M* (haloes of a given mass tend to be older in clusters and younger in voids) and are independent of it for larger masses; ii) Low-mass haloes in clusters are generally less spherical and more oblate than in other regions; iii) Low-mass haloes in clusters have a higher median spin than in filaments and present a more prominent fraction of rapidly spinning objects; we identify recent major mergers as a likely source of this effect. For all these relations, we provide accurate functional fits as a function of halo mass and environment. We also look for correlations between halo-spin directions and the large-scale structures: the strongest effect is seen in sheets where halo spins tend to lie within the plane of symmetry of the mass distribution. Finally, we measure the spatial auto-correlation of spin directions and the cross-correlation between the directions of intrinsic and orbital angular momenta of neighbouring haloes. While the first quantity is always very small, we find that spin-orbit correlations are rather strong especially for low-mass haloes in clusters and high-mass haloes in filaments.Comment: 13 pages, 13 figures. Version accepted for publication in MNRAS (references added). Version with high-resolution figures available at http://www.exp-astro.phys.ethz.ch/hahn/pub/HPCD06.pd