Abstract
AbstractNano-optic imagers that modulate light at sub-wavelength scales could enable new applications in diverse domains ranging from robotics to medicine. Although metasurface optics offer a path to such ultra-small imagers, existing methods have achieved image quality far worse than bulky refractive alternatives, fundamentally limited by aberrations at large apertures and low f-numbers. In this work, we close this performance gap by introducing a neural nano-optics imager. We devise a fully differentiable learning framework that learns a metasurface physical structure in conjunction with a neural feature-based image reconstruction algorithm. Experimentally validating the proposed method, we achieve an order of magnitude lower reconstruction error than existing approaches. As such, we present a high-quality, nano-optic imager that combines the widest field-of-view for full-color metasurface operation while simultaneously achieving the largest demonstrated aperture of 0.5 mm at an f-number of 2.
Funder
National Science Foundation
United States Department of Defense | Defense Advanced Research Projects Agency
Publisher
Springer Science and Business Media LLC
Subject
General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry
Reference36 articles.
1. Engelberg, J. & Levy, U. The advantages of metalenses over diffractive lenses. Nat. Commun. 11, 1991 (2020).
2. Lin, D., Fan, P., Hasman, E. & Brongersma, M. L. Dielectric gradient metasurface optical elements. Science 345, 298–302 (2014).
3. Mait, J. N., Athale, R. A., van der Gracht, J. & Euliss, G. W. Potential applications of metamaterials to computational imaging. In Proc. Frontiers in Optics/Laser Science, FTu8B.1 (Optical Society of America, 2020).
4. Peng, Y. et al. Learned large field-of-view imaging with thin-plate optics. ACM Trans. Graph. 38, 219 (2019).
5. Yu, N. & Capasso, F. Flat optics with designer metasurfaces. Nat. Mat. 13, 139–150 (2014).
Cited by
114 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献