Showing papers by "Nabila Aghanim published in 2007"
TL;DR: The Cosmic Microwave Background fluctuations provide a powerful probe of the dark ages of the universe through the imprint of the secondary anisotropies associated with the reionisation of universe and the growth of structure as mentioned in this paper.
Abstract: The Cosmic Microwave Background fluctuations provide a powerful probe of the dark ages of the universe through the imprint of the secondary anisotropies associated with the reionisation of the universe and the growth of structure. We review the relation between the secondary anisotropies and and the primary anisotropies that are directly generated by quantum fluctuations in the very early universe. The physics of secondary fluctuations is described, with emphasis on the ionisation history and the evolution of structure. We discuss the different signatures arising from the secondary effects in terms of their induced temperature fluctuations, polarisation and statistics. The secondary anisotropies are being actively pursued at present, and we review the future and current observational status.
8 citations
18 Apr 2007
TL;DR: This work addresses the question of finding and discriminating between the different non-Gaussian signatures using both wavelet and curvelet transforms on the sphere to analyse simulated data in the PLANCK experiment.
Abstract: One of the goals in cosmology is to understand the formation and evolution of the structures resulting from the growth of initial density perturbations. Recent Cosmic Microwave Background (CMB) observations indicate that the latter essentially came out of Gaussian distributed quantum fluctuations in the inflationary scenario. However, topological defects (e.g. cosmic strings) could contribute to the signal. One of their important footprint would be the predicted non-Gaussian distribution of the temperature anisotropies. In addition, other sources of non-Gaussian signatures do contribute to the signal, in particular the Sunyaev-Zel’dovich effect of galaxy clusters[01]. In this general context and motivated by the PLANCK experiment, we address the question of finding and discriminating between the different non-Gaussian signatures using both wavelet and curvelet transforms on the sphere to analyse simulated data.
TL;DR: In this paper, a sparsity-based component separation method is proposed for CMB data called Generalized Morphological Component Analysis (GMCA), which is formulated in a Bayesian maximum a posteriori (MAP) framework.
Abstract: In the last decade, the study of cosmic microwave background (CMB) data has become one of the most powerful tools to study and understand the Universe. More precisely, measuring the CMB power spectrum leads to the estimation of most cosmological parameters. Nevertheless, accessing such precious physical information requires extracting several different astrophysical components from the data. Recovering those astrophysical sources (CMB, Sunyaev-Zel'dovich clusters, galactic dust) thus amounts to a component separation problem which has already led to an intense activity in the field of CMB studies. In this paper, we introduce a new sparsity-based component separation method coined Generalized Morphological Component Analysis (GMCA). The GMCA approach is formulated in a Bayesian maximum a posteriori (MAP) framework. Numerical results show that this new source recovery technique performs well compared to state-of-the-art component separation methods already applied to CMB data.