Dispersion engineered metasurfaces for broadband, high-NA, high-efficiency, dual-polarization analog image processing

Michele Cotrufo (), Akshaj Arora, Sahitya Singh and Andrea Alù ()
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Michele Cotrufo: City University of New York
Akshaj Arora: City University of New York
Sahitya Singh: City University of New York
Andrea Alù: City University of New York

Nature Communications, 2023, vol. 14, issue 1, 1-9

Abstract: Abstract Optical metasurfaces performing analog image processing – such as spatial differentiation and edge detection – hold the potential to reduce processing times and power consumption, while avoiding bulky 4 F lens systems. However, current designs have been suffering from trade-offs between spatial resolution, throughput, polarization asymmetry, operational bandwidth, and isotropy. Here, we show that dispersion engineering provides an elegant way to design metasurfaces where all these critical metrics are simultaneously optimized. We experimentally demonstrate silicon metasurfaces performing isotropic and dual-polarization edge detection, with numerical apertures above 0.35 and spectral bandwidths of 35 nm around 1500 nm. Moreover, we introduce quantitative metrics to assess the efficiency of these devices. Thanks to the low loss nature and dual-polarization response, our metasurfaces feature large throughput efficiencies, approaching the theoretical maximum for a given NA. Our results pave the way for low-loss, high-efficiency and broadband optical computing and image processing with free-space metasurfaces.

Date: 2023
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DOI: 10.1038/s41467-023-42921-z

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