Jan Michael Kratochvil
University of Miami
Abstract:
In two recent papers we study the cosmological origin of peaks in weak gravitational lensing (WL) convergence maps, and show that Minkowski Functionals (MFs) of WL maps contain significant non-Gaussian, cosmology-dependent information. To do this, we produce a large suite of cosmological ray-tracing N-body simulations to create mock WL convergence maps. For the origin of the peaks, we study which halos in the simulations get pierced by which light rays in the WL maps. For the MF constraints, we study the cosmological information content of MFs derived from these maps. Our suite consists of 80 independent 512^3-particle N-body runs, covering seven different cosmologies, varying three cosmological parameters Omega_m, w, and sigma_8 one at a time, around a fiducial LambdaCDM model. In each cosmology, we use ray-tracing to create a thousand pseudo-independent 12 deg^2 convergence maps, and use these in a Monte Carlo procedure to estimate the joint confidence contours on the above three parameters. We include redshift tomography at three different source redshifts z_s=1, 1.5, 2, explore five different smoothing scales theta_G=1, 2, 3, 5, 10 arcmin, and explicitly compare and combine the MFs with the WL power spectrum. We find that the MFs capture a substantial amount of information from non-Gaussian features of convergence maps, i.e. beyond the power spectrum. The MFs are particularly well suited to break degeneracies and to constrain the dark energy equation of state parameter w (by a factor of ~ three better than from the power spectrum alone). The non-Gaussian information derives partly from the one-point function of the convergence (through V_0, the "area" MF), and partly through non-linear spatial information (through combining different smoothing scales for V_0, and through V_1 and V_2, the boundary length and genus MFs, respectively). In contrast to the power spectrum, the best constraints from the MFs are obtained only when multiple smoothing scales are combined.