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(Peer-Reviewed) Reconfigurable optical neural networks with Plug-and-Play metasurfaces
Yongmin Liu ¹ ², Yuxiao Li ²
¹ Department of Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts 02115, USA
² Department of Electrical and Computer Engineering, Northeastern University, Boston, Massachusetts 02115, USA
Opto-Electronic Advances, 2024-06-04
https://doi.org/10.29026/oea.2024.240057
https://www.oejournal.org/article/doi/10.29026/oea.2024.240057
Abstract

In a very recent study, Prof. Lingling Huang and co-workers proposed and demonstrated reconfigurable optical neural networks based on cascaded metasurfaces. By fixing one metasurface and switching the other pluggable metasurfaces, the neural networks, which operate at near-infrared wavelengths, can perform distinct recognition tasks for handwritten digits and fashion products. This innovative device opens up an avenue for all-optical, high-speed, low-power, and multi-functional artificial intelligence systems.
Reconfigurable optical neural networks with Plug-and-Play metasurfaces_1
Reconfigurable optical neural networks with Plug-and-Play metasurfaces_2
Reconfigurable optical neural networks with Plug-and-Play metasurfaces_3
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    • Paving continuous heat dissipation pathways for quantum dots in polymer with orange-inspired radially aligned UHMWPE fibers                                Multiplexed stimulated emission depletion nanoscopy (mSTED) for 5-color live-cell long-term imaging of organelle interactome
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