Metasurface on integrated photonic platform: from mode converters to machine learning
| Author(s) | Wang, Zi | |
| Author(s) | Xiao, Yahui | |
| Author(s) | Liao, Kun | |
| Author(s) | Li, Tiantian | |
| Author(s) | Song, Hao | |
| Author(s) | Chen, Haoshuo | |
| Author(s) | Uddin, S. M. Zia | |
| Author(s) | Mao, Dun | |
| Author(s) | Wang, Feifan | |
| Author(s) | Zhou, Zhiping | |
| Author(s) | Yuan, Bo | |
| Author(s) | Jiang, Wei | |
| Author(s) | Fontaine, Nicolas K. | |
| Author(s) | Agrawal, Amit | |
| Author(s) | Willner, Alan E. | |
| Author(s) | Hu, Xiaoyong | |
| Author(s) | Gu, Tingyi | |
| Date Accessioned | 2022-08-08T15:39:43Z | |
| Date Available | 2022-08-08T15:39:43Z | |
| Publication Date | 2022-07-20 | |
| Description | This article was originally published in Nanophotonics. The version of record is available at: https://doi.org/10.1515/nanoph-2022-0294 | en_US |
| Abstract | Integrated photonic circuits are created as a stable and small form factor analogue of fiber-based optical systems, from wavelength-division multiplication transceivers to more recent mode-division multiplexing components. Silicon nanowire waveguides guide the light in a 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 in the integrated photonic platform, using arrays of subwavelength meta-atoms or metalines for guiding the diffraction and interference of light. The integrated metasurface system mimics free-space optics, where on-chip analogues of basic optical components are developed with foundry compatible geometry, such as low-loss lens, spatial-light modulator, and other wavefront shapers. We discuss the role of metasurface in integrated photonic signal processing 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 framework, toward optical neural networks and analog photonic accelerators. | en_US |
| Sponsor | This work was supported by DARPA (N660012114034) and Jiangsu Innovation Team, National Natural Science Foundation of China (Grant 61775094). | en_US |
| Citation | Wang, Zi, Xiao, Yahui, Liao, Kun, Li, Tiantian, Song, Hao, Chen, Haoshuo, Uddin, S. M. Zia, Mao, Dun, Wang, Feifan, Zhou, Zhiping, Yuan, Bo, Jiang, Wei, Fontaine, Nicolas K., Agrawal, Amit, Willner, Alan E., Hu, Xiaoyong and Gu, Tingyi. "Metasurface on integrated photonic platform: from mode converters to machine learning" Nanophotonics , no. (2022). https://doi.org/10.1515/nanoph-2022-0294 | en_US |
| ISSN | 2192-8614 | |
| URL | https://udspace.udel.edu/handle/19716/31173 | |
| Language | en_US | en_US |
| Publisher | Nanophotonics | en_US |
| Keywords | deep learning | en_US |
| Keywords | metasurface | en_US |
| Keywords | silicon photonics | en_US |
| Title | Metasurface on integrated photonic platform: from mode converters to machine learning | en_US |
| Type | Article | en_US |
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