All-optical ultrafast ReLU function for energy-efficient nanophotonic deep learning
Abstract: In recent years, the computational demands of deep learning applications have necessitated the introduction of energy-efficient hardware accelerators. Optical neural networks are a promising option; however, thus far they have been largely limited by the lack of energy-efficient nonlinear optical functions. Here, we experimentally demonstrate an all-optical Rectified Linear Unit (ReLU), which is the most widely used nonlinear activation function for deep learning, using a periodically-poled thin-film lithium niobate nanophotonic waveguide and achieve ultra-low energies in the regime of femtojoules per activation with near-instantaneous operation. Our results provide a clear and practical path towards truly all-optical, energy-efficient nanophotonic deep learning.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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All-optical ultrafast ReLU function for energy-efficient nanophotonic deep learning ; volume:12 ; number:5 ; year:2022 ; pages:847-855 ; extent:9
Nanophotonics ; 12, Heft 5 (2022), 847-855 (gesamt 9)
- Urheber
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Li, Gordon H.Y.
Sekine, Ryoto
Nehra, Rajveer
Gray, Robert M.
Ledezma, Luis
Guo, Qiushi
Marandi, Alireza
- DOI
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10.1515/nanoph-2022-0137
- URN
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urn:nbn:de:101:1-2023030913393772437617
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 11:03 MESZ
Datenpartner
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Beteiligte
- Li, Gordon H.Y.
- Sekine, Ryoto
- Nehra, Rajveer
- Gray, Robert M.
- Ledezma, Luis
- Guo, Qiushi
- Marandi, Alireza