Perspective on 3D vertically-integrated photonic neural networks based on VCSEL arrays
Abstract: The rapid development of artificial intelligence has stimulated the interest in the novel designs of photonic neural networks. As three-dimensional (3D) neural networks, the diffractive neural networks (DNNs) relying on the diffractive phenomena of light, has demonstrated their superb performance in the direct parallel processing of two-dimensional (2D) optical data at the speed of light. Despite the outstanding achievements, DNNs utilize centimeter-scale devices to generate the input data passively, making the miniaturization and on-chip integration of DNNs a challenging task. Here, we provide our perspective on utilizing addressable vertical-cavity surface-emitting laser (VCSEL) arrays as a promising data input device and integrated platform to achieve compact, active DNNs for next-generation on-chip vertical-stacked photonic neural networks. Based on the VCSEL array, micron-scale 3D photonic chip with a modulation bandwidth at tens of GHz can be available. The possible future directions and challenges of the 3D photonic chip are analyzed.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Perspective on 3D vertically-integrated photonic neural networks based on VCSEL arrays ; volume:12 ; number:5 ; year:2023 ; pages:827-832 ; extent:6
Nanophotonics ; 12, Heft 5 (2023), 827-832 (gesamt 6)
- Creator
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Gu, Min
Dong, Yibo
Yu, Haoyi
Luan, Haitao
Zhang, Qiming
- DOI
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10.1515/nanoph-2022-0437
- URN
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urn:nbn:de:101:1-2023030913411441259294
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
- 14.08.2025, 10:48 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Gu, Min
- Dong, Yibo
- Yu, Haoyi
- Luan, Haitao
- Zhang, Qiming
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