TO: BAYESIAN STRONG-LENS MODELLING: SUBSTRUCTURE IN MASSIVE GALAXIES
SESZIONE DI TORINO
The LCDM cosmological model for structure formation has been very successful in explaining many of the observed properties of the Universe on large scales and at different cosmic epochs. However several important issues remain unsolved on smaller scale. Among the most puzzling discrepancies is the so-called missing satellites problem. As observed in numerical cosmological simulations, the LCDM scenario predicts a number of substructures within the Local Group which is 1-2 orders of magnitude higher than what is effectively observed. A number of possible solutions has been proposed to alleviate this problem. One of the most popular astrophysical solutions relies on the inability of low-mass satellites to form stars, either by supernova feedback, photoionization or reionization. The gas collapse/cooling suppression sensibly reduces the number of visible satellites; if indeed these high M/L substructures exist, gravitational lensing provides us with a powerful tool to explore CDM substructures in galaxies outside the Local Group and at a relative high redshift. I will present a fully non-parametric Bayesian methodology of gravitational imaging which we recently developed and show how substructure in lens galaxies can be detected with these techniques. I will present some preliminary results when applied to Sloan Lens ACS (SLACS) lens systems.

DATA: 11-04-2008

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