Abstract
A hybrid inverse design framework is proposed for the efficient design of ultra broadband achromatic metalenses with very simple resonant structures. The framework combines a data-driven inverse dispersion engineering approach along with an optimal random spatial multiplexing (ORSM) method. The two-stage framework is based on a design strategy that segments the entire operating band into multiple subbands and performs continuous achromatic design within each subband. As a result, the framework alleviates the phase dispersion requirements imposed on meta-atoms by conventional dispersion engineering for ultra broadband operation, which typically necessitates complex and time-consuming meta-atom design. The inverse dispersion engineering, trained on a compact dataset of only 792 samples, accurately predicts meta-atom structures with desired phase and amplitude responses. Subsequently, the ORSM method optimizes the spatial arrangement of the inverse-designed meta-atoms, ultimately generating the final metalens layout. To validate the performance of the proposed framework, a reflective microwave ultra broadband metalens is designed, simulated, and characterized. The experimental results demonstrate achromatic focusing with a focal length of 215 mm and an average focusing efficiency of 62.73% over the operating band of 8–16 GHz. This method could pave a new way for the development of achromatic meta-devices for wideband microwave applications.
| Original language | English |
|---|---|
| Pages (from-to) | 7816-7829 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Antennas and Propagation |
| Volume | 73 |
| Issue number | 10 |
| DOIs | |
| State | Published - 2025 |
Keywords
- Deep neural networks (DNNs)
- dispersion engineering
- inverse design
- spatial multiplexing
- ultra broadband achromatic metalenses
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