Journal
OPTICS LETTERS
Volume 46, Issue 22, Pages 5735-5738Publisher
OPTICAL SOC AMER
DOI: 10.1364/OL.439393
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Funding
- MIT Skoltech Seed Fund Program
- DARPA EXTREME Optics and Imaging Program [HR00111720029]
- Lockheed Martin Corporation Internal Research and Development
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The direct search method adapted for metasurface optimization, paired with deep learning techniques for free-form meta-atom generation, provides computationally efficient approaches for metasurface optics. The optimized achromatic metalenses designed using this method exhibit superior broadband performances compared to traditional diffractive counterparts. Additionally, an achromatic and wide-field-of-view metalens design is demonstrated in the study.
In this Letter, we adapt the direct search method to metasurface optimization. We show that the direct search algorithm, when coupled with deep learning techniques for free-form meta-atom generation, offers a computationally efficient optimization approach for metasurface optics. As an example, we apply the approach to optimization of achromatic metalenses. Taking advantage of the diverse dispersion responses of free-form meta-atoms, metalenses designed using this approach exhibit superior broadband performances compared to their multilevel diffractive counterparts. We further demonstrate an achromatic and wide-field-of-view metalens design. (C) 2021 Optical Society of America
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