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20 August 2020 Incorporation of robust constraints in globally optimized metasurfaces
Jonathan A. Fan
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Proceedings Volume 11460, Metamaterials, Metadevices, and Metasystems 2020; 114601D (2020) https://doi.org/10.1117/12.2571080
Event: SPIE Nanoscience + Engineering, 2020, Online Only
Abstract
Inverse design using topology optimization has proven to be highly effective to design metasurfaces with high performance. In particular, adjoint-based gradient computations can iteratively dielectric distributions to perform local optimization of freeform devices, and these computations can be incorporated into global topology optimizers such as GLOnets. A major challenge is incorporating fabricability constraints, such as the enforcement of the minimum feature size of the pattern, such that the final design is compatible with experimental lithography and etching steps. We introduce a conceptually new method that allows us to accurately impose constraints through reparametrization. The pixelated device pattern is reparametrized by a new set of parameters where design constraints are naturally and robustly incorporated. Updates to this new reparametrized latent space during the optimization are achieved using backpropagation. We demonstrate the effectiveness of this scheme by design
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Jonathan A. Fan "Incorporation of robust constraints in globally optimized metasurfaces", Proc. SPIE 11460, Metamaterials, Metadevices, and Metasystems 2020, 114601D (20 August 2020); https://doi.org/10.1117/12.2571080
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KEYWORDS
Data processing
Dielectrics
Etching
Image processing
Lithography
Optimization (mathematics)
Silicon
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