Differentiable Inverse Design of Free- Form Meta-optics Using Multiplicative Filter Network
2024 INTERNATIONAL APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY SYMPOSIUM, ACES 2024（2024）
Abstract
Recent developments in automatic differentiation enhance the inverse design methodologies for optimizing flexible and free-form meta-optical devices. This study introduces an inverse design framework that merges a fully differentiable rigorous diffraction interface theory solver with a multiplicative filter network, serving as a generator for free-form meta-atoms. The simulation outcomes confirm that our framework effectively meets its design objectives, optimizing two wide-band mid-infrared beam deflectors for TE and TM modes and enhancing transmission efficiencies to as much as 80% at target wavelengths.
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Key words
inverse design,automatic differentiation,R-DIT,MFN,torchrdit,implicit neural representation
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