Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Metasurface on integrated photonic platform: from mode converters to machine learning

Published

Author(s)

Zi Wang, Yahui Xiao, Kun Liao, Tiantian Li, Hao Song, Haoshuo Chen, S M Zia Uddin, Dun Mao, Feifan Wang, Zhiping Zhou, Bo Yuan, Wei Jiang, Nikolas Fontaine, Amit Agrawal, Alan Willner, Xiaoyong Yu, Tingyi Gu

Abstract

Integrated photonic circuits are created as a small form factor and robust analogue for fiber-based optical systems, from wavelength-division multiplication transceivers to more recent mode-division multiplex-ing components. Silicon nanowire waveguides guide the light in the way that single and few mode fibers define the direction of signal flow. Beyond communication tasks, on-chip cascaded interferometers and photonic meshes are also sought for optical computing and advanced signal processing technology. Here we review an alternative way of defining the light flow on the integrated photonic platform, with arrays of subwavelength meta-atoms or metalines for guiding the diffraction and interference of light. The inte-grated metasurface system mimics the free-space optics, where the on-chip analogue of basic compo-nents are developed with foundry compatible geometry, such as low loss lens, spatial-light modulator and other wave-front shapers. We discuss the role of metasurface in integrated photonic signal pro-cessing systems, introduce the design principles of such metasurface systems for low loss compact mode conversion, mathematical operation, diffractive optical systems for hyperspectral imaging, and tuning schemes of metasurface systems. Then we perceive reconfigurability schemes for metasurface frame-work, towards optical neuron networks and analogue photonic accelerators.
Citation
Nanophotonics
Volume
11
Issue
16

Citation

Wang, Z. , Xiao, Y. , Liao, K. , Li, T. , Song, H. , Chen, H. , Uddin, S. , Mao, D. , Wang, F. , Zhou, Z. , Yuan, B. , Jiang, W. , Fontaine, N. , Agrawal, A. , Willner, A. , Yu, X. and Gu, T. (2022), Metasurface on integrated photonic platform: from mode converters to machine learning, Nanophotonics, [online], https://doi.org/10.1515/nanoph-2022-0294 , https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934965 (Accessed November 29, 2022)
Created July 20, 2022, Updated August 25, 2022