Fast and accurate electromagnetic simulation of large-area metasurfaces remains a major obstacle in automating their design.In this paper,we propose a metasurface simulation distribution strategy which achieves a line...Fast and accurate electromagnetic simulation of large-area metasurfaces remains a major obstacle in automating their design.In this paper,we propose a metasurface simulation distribution strategy which achieves a linear reduction in the simulation time with the number of compute nodes.Combining this distribution strategy with a GPU-based implementation of the Transition-matrix method,we perform accurate simulations and adjoint sensitivity analysis of large-area metasurfaces.We demonstrate ability to perform a distributed simulation of large-area metasurfaces(over 600λ×600λ),while accurately accounting for scatterer-scatterer interactions significantly beyond the locally periodic approximation.展开更多
基金This work was supported by the Samsung GRO program.J.S.acknowledges support from the National Science Foundation Graduate Research Fellowship(grant no.DGE-1656518)Cisco Systems Stanford Graduate Fellowship(SGF)R.T acknowledges support from Max Planck Harvard research center for Quantum Optics(MPHQ)fellowship,and Sarah and Kailath Stanford Graduate Fellowship(SGF).
文摘Fast and accurate electromagnetic simulation of large-area metasurfaces remains a major obstacle in automating their design.In this paper,we propose a metasurface simulation distribution strategy which achieves a linear reduction in the simulation time with the number of compute nodes.Combining this distribution strategy with a GPU-based implementation of the Transition-matrix method,we perform accurate simulations and adjoint sensitivity analysis of large-area metasurfaces.We demonstrate ability to perform a distributed simulation of large-area metasurfaces(over 600λ×600λ),while accurately accounting for scatterer-scatterer interactions significantly beyond the locally periodic approximation.
