Advanced computational design of complex nanostructured photonic devices using high order discontinuous Galerkin methods and statistical learning global optimization
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Nanophotonics is the science that studies the interactions of light with matter at the nanoscale. Indeed, nanostructuring of materials has paved the way for manipulating and enhancing light-matter interactions, thereby opening the door for the full control of these interactions at the nanoscale. Nanophotonics encompasses a wide variety of topics, including metamaterials, plasmonics, high resolution imaging, quantum nanophotonics and functional photonic materials. Previously viewed as a largely academic field, nanophotonics is now entering the mainstream, and will play a major role in the development of exciting new products, ranging from high efficiency solar cells to personalized health monitoring devices able to detect the chemical composition of molecules at ultra-low concentrations. In this talk, we present our recent efforts and achievements toward the development of innovative numerical methodologies for the design of nanoscale photonic devices. Numerical modeling plays a crucial role in this context, in particular for discovering non-intuitive nanostructures or material nanostructuring for harvesting and tailoring the interaction of light with matter at the nanoscale. In our works, we combine two main numerical ingredients: (1) high order Discontinuous Galerkin methods for solving the system of time-domain or frequency-domain Maxwell equations in 3D coupled to appropriate differential models of physical dispersion in photonic materials and (2) one of the most advanced optimization techniques that belongs to the class of Bayesian optimization and is known as Efficient Global Optimization (EGO). We report on recent extensions and applications of this methodology to deal with improving the light absorption in ultra-thin solar cells and nanostructured CMOS imager pixels.