Diffusion-Based Electromagnetic Inverse Design of Scattering Structured Media
This addresses the time-consuming optimization bottleneck in designing metasurfaces for photonic and wireless communication systems, though it appears incremental as an application of diffusion models to a specific domain.
The paper tackles the electromagnetic inverse design problem by developing a conditional diffusion model that generates structured media geometries directly from target scattering patterns, achieving median MPE below 19% (best 1.39%) and reducing design time from hours to seconds compared to evolutionary optimization.
We present a conditional diffusion model for electromagnetic inverse design that generates structured media geometries directly from target differential scattering cross-section profiles, bypassing expensive iterative optimization. Our 1D U-Net architecture with Feature-wise Linear Modulation learns to map desired angular scattering patterns to 2x2 dielectric sphere structure, naturally handling the non-uniqueness of inverse problems by sampling diverse valid designs. Trained on 11,000 simulated metasurfaces, the model achieves median MPE below 19% on unseen targets (best: 1.39%), outperforming CMA-ES evolutionary optimization while reducing design time from hours to seconds. These results demonstrate that employing diffusion models is promising for advancing electromagnetic inverse design research, potentially enabling rapid exploration of complex metasurface architectures and accelerating the development of next-generation photonic and wireless communication systems. The code is publicly available at https://github.com/mikzuker/inverse_design_metasurface_generation.