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We present a statistical study of the effects induced by substructures on the deflection potential of dark matter halos in the strong lensing regime. This investigation is based on the pertubative solution around the Einstein radius (Alard 2007) in which all the information on the deflection potential is specified by only a pair of one-dimensional functions on this ring. Using direct comparison with ray-tracing solutions, we found that the iso-contours of lensed images predicted by the pertubative solution is reproduced with a mean error on their radial extension of less than 1% - in units of the Einstein radius, for reasonable substructure masses. It demonstrates the efficiency of the approximation to track possible signatures of substructures. We have evaluated these two fields and studied their properties for different lens configurations modelled either through massive dark matter halos from a cosmological N-body simulation, or via toy models of Monte Carlo distribution of substructures embedded in a triaxial Hernquist potential. As expected, the angular power spectra of these two fields tend to have larger values for larger harmonic numbers when substructures are accounted for and they can be approximated by power-laws, whose values are fitted as a function of the profile and the distribution of the substructures.
We use the SPARC code for MHD simulations with monolithic flux tubes of varying subsurface topology. Our studies involve the interactions of waves caused by a single source with subsurface magnetic fields. Mode conversion causing acoustic power to tr
Transport properties of irradiated graphene (electrical conductivity and mobility) are numerically investigated using the real-space Kubo formalism. A micrometer-sized system consisting of millions of atoms with nanopores of various sizes and concent
We aim to study a finite volume scheme to solve the two dimensional inviscid primitive equations of the atmosphere with humidity and saturation, in presence of topography and subject to physically plausible boundary conditions to the system of equati
Efficiently predicting the flowfield and load in aerodynamic shape optimisation remains a highly challenging and relevant task. Deep learning methods have been of particular interest for such problems, due to their success for solving inverse problem
We investigate the renormalization of a class of gauge-invariant nonlocal quark bilinear operators, including a finite-length Wilson-line (called Wilson-line operators). The matrix elements of these operators are involved in the recent quasi-distribu