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Abstract:

We present the first high-resolution N-body simulations of the fragmentation of dark matter filaments. Such fragmentation occurs in top-down scenarios of structure formation, when the dark matter is warm instead of cold. In a previous paper, we showed that warm dark matter (WDM) differs from the standard cold dark matter (CDM) mainly in the formation history and large-scale distribution of low-mass haloes, which form later and tend to be more clustered in WDM than in CDM universes, tracing the filamentary structures of the cosmic web more closely. Therefore, we focus our computational effort in this paper on one particular filament extracted from a WDM cosmological simulation and compare in detail its evolution to that of the same CDM filament. We find that the mass distribution of the haloes forming via fragmentation within the filament is broadly peaked around a Jeans mass of a few 109 M ⊙, corresponding to a gravitational instability of smooth regions with an overdensity contrast around 10 at these redshifts. Our results confirm that WDM filaments fragment and form gravitationally bound haloes in a top-down fashion, whereas CDM filaments are built bottom-up, thus demonstrating the impact of the nature of the dark matter on dwarf galaxy properties.

Abstract:

MAXIMA is a balloon-borne platform for measuring the anisotropy of the Cosmic Microwave Background (CMB). It has measured the CMB power spectrum with a 10-arcmin FWHM beam, corresponding to a detection of the power spectrum out to spherical harmonic multipole l similar to 1000. The spectrum is consistent with a flat Universe with a nearly scale-invariant initial spectrum of adiabatic density fluctuations. Moreover, the MAXIMA data are free from any notable non-Gaussian contamination and from foreground dust emission. In the same region, the WMAP experiment observes the same structure as that observed by MAXIMA, as evinced by analysis of both maps and power spectra. The next step in the evolution of the MAXIMA program is MAXIPOL, which will observe the polarization of the CMB with comparable resolution and high sensitivity over a small patch of the sky. (C) 2003 Elsevier B.V. All rights reserved.

Abstract:

We review methods for detecting microwave background non-Gaussianity based on the three-point function in harmonic space-the bispectrum. We concentrate on two methods, one of which is optimised to minimise the error bars on bispectrum estimates, and the other, the pseudo-bispectrum, which is more straighforward to calculate, but which has larger error bars. Application to the MAXIMA dataset shows the map is consistent with Gaussian, with measurements of the weak non-Gaussianity parameter given by the two methods as f(NL)=1500+/-950 and f(NL)=2700+/-1650, respectively. (C) 2003 Elsevier B.V. All rights reserved.

Abstract:

We report on measurements of the cosmological constant, Lambda, and the redshift space distortion parameter beta=Omega_m^0.6/b, based on an analysis of the QSO power spectrum parallel and perpendicular to the observer's line of sight, from the final catalogue of the 2dF QSO Redshift Survey. We derive a joint Lambda - beta constraint from the geometric and redshift-space distortions in the power spectrum. By combining this result with a second constraint based on mass clustering evolution, we break this degeneracy and obtain strong constraints on both parameters. Assuming a flat cosmology and a Lambda cosmology r(z) function to convert from redshift into comoving distance, we find best fit values of Omega_Lambda=0.71^{+0.09}_{-0.17} and beta(z~1.4)=0.45^{+0.09}_{-0.11}. Assuming instead an EdS cosmology r(z) we find that the best fit model obtained, with Omega_Lambda=0.64^{+0.11}_{-0.16} and beta(z~1.4)=0.40^{+0.09}_{-0.09}, is consistent with the Lambda r(z) results, and inconsistent with a Lambda=0 flat cosmology at over 95 per cent confidence.

Abstract:

We review selected methods of the Cosmic Microwave Background data analysis appropriate for the analysis of the largest currently available data sets. We focus on techniques of the time-ordered data manipulation and map making algorithms based on the maximum-likelihood approach. The presented methods have been applied to the MAXIMA data analysis (Hanany et al 2000) and the description of the algorithms is illustrated with the examples drawn from that experience. The more extensive presentation of the here-mentioned issues will be given in the forthcoming paper (Stompor et al 2001).