We present results from a comprehensive lensing analysis in HST data, of the complete CLASH cluster sample. We identify new multiple-images previously undiscovered allowing improved or first constraints on the cluster inner mass distributions and pro
files. We combine these strong-lensing constraints with weak-lensing shape measurements within the HST FOV to jointly constrain the mass distributions. The analysis is performed in two different common parameterizations (one adopts light-traces-mass for both galaxies and dark matter while the other adopts an analytical, elliptical NFW form for the dark matter), to provide a better assessment of the underlying systematics - which is most important for deep, cluster-lensing surveys, especially when studying magnified high-redshift objects. We find that the typical (median), relative systematic differences throughout the central FOV are $sim40%$ in the (dimensionless) mass density, $kappa$, and $sim20%$ in the magnification, $mu$. We show maps of these differences for each cluster, as well as the mass distributions, critical curves, and 2D integrated mass profiles. For the Einstein radii ($z_{s}=2$) we find that all typically agree within $10%$ between the two models, and Einstein masses agree, typically, within $sim15%$. At larger radii, the total projected, 2D integrated mass profiles of the two models, within $rsim2arcmin$, differ by $sim30%$. Stacking the surface-density profiles of the sample from the two methods together, we obtain an average slope of $dlog (Sigma)/dlog(r)sim-0.64pm0.1$, in the radial range [5,350] kpc. Lastly, we also characterize the behavior of the average magnification, surface density, and shear differences between the two models, as a function of both the radius from the center, and the best-fit values of these quantities.
According to the current standard model of Cosmology, matter in the Universe arranges itself along a network of filamentary structure. These filaments connect the main nodes of this so-called Cosmic Web, which are clusters of galaxies. Although its l
arge-scale distribution is clearly characterized by numerical simulations, constraining the dark matter content of the cosmic web in reality turns out to be difficult. The natural method of choice is gravitational lensing. However, the direct detection and mapping of the elusive filament signal is challenging and in this work we present two methods,specifically tailored to achieve this task. A linear matched filter aims at the detection of the smooth mass component of filaments and is optimized to perform a shear decomposition that follows the anisotropic component of the lensing signal. Filaments clearly inherit this property due to their morphology. At the same time, the contamination arising from the central massive cluster is controlled in a natural way. The filament 1 {sigma} detection is of about {kappa} ~ 0.01-0.005 according to the filters template width and length, enabling the detection of structures out of reach with other approaches. The second, complementary method seeks to detect the clumpy component of filaments. The detection is determined by the number density of sub-clump identifications in an area enclosing the potential filament, as it was found within the observed field with the filter approach. We test both methods against Mock observations based on realistic N-Body simulations of filamentary structure and prove the feasibility of detecting filaments with ground-based data.
