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3D Dark Matter and Stellar Mass Mapping of Wide Field Imaging Survey (3D-Maps)
Date du début: 1 sept. 2013, Date de fin: 31 août 2015 PROJET  TERMINÉ 

The project we are proposing here aims at building three-dimensional (3D) dark matter and stellar mass maps of the full Stripe82 area in a way similar to the 3D COSMOS maps, but in a redshift range from 0.2 to 0.6, and focusing on more massive cluster systems that are absent from the COSMOS survey due to its limited field of view. The ultimate goal is to use this 3D map to put strong constraints on cosmology.From the CFHT raw data, we can measure the galaxy shapes not only with existing techniques, but also with new competitive algorithms, which lead to some of the best results when applied to the synthetic data of the GREAT10 image processing challenge. It is now both timely and important to use these new tools on real data and to reconstruct the 2D shear field of intervening mass, projected along the line of sight. The 3D dark matter map, and hence its time-dependent growth, can be visualized by splitting the background source galaxies into discrete redshift bins. We can identify the largest mass clumps at different redshifts of Stripe82 from the 3D maps. Using the derived stellar masses by the NIR data from the VISTA/VIRCAM and CFHT/WIRACAM survey, we can compare it to the 3D dark matter map, as well as generate 3D dark matter and stellar mass maps of the whole Stripe82 area. Then, we will compare with the optical and SZ (and in the future X-ray) cluster catalogs. Furthermore, we will use stacked weak lensing technique to measure the dark matter profiles of massive structures. For stacking analysis, we will use cluster galaxy stellar mass as proxy, which allow us also to use the halo model formalism to model the stacked signal. All the above goals are made possible mostly due to the broad wavelength coverage of CS82 and to its huge field of view imaged in the optical at high spatial resolution.With this project, we will pave the way to constrain the cosmological models using the future survey such as DES, HSC, LSST and Euclid.