All-optical computing with beyond 100-GHz clock rates
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arXiv
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866913665035272192 |
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| author | Li, Gordon H. Y. Parto, Midya Ge, Jinhao Ji, Qing-Xin Gao, Maodong Yu, Yan Williams, James Gray, Robert M. Leefmans, Christian R. Englebert, Nicolas Vahala, Kerry J. Marandi, Alireza |
| author_facet | Li, Gordon H. Y. Parto, Midya Ge, Jinhao Ji, Qing-Xin Gao, Maodong Yu, Yan Williams, James Gray, Robert M. Leefmans, Christian R. Englebert, Nicolas Vahala, Kerry J. Marandi, Alireza |
| contents | A computer's clock rate ultimately determines the minimum time between sequential operations or instructions. Despite exponential advances in electronic computer performance owing to Moore's Law and increasingly parallel system architectures, computer clock rates have remained stagnant at $\sim5~\mathrm{GHz}$ for almost two decades. This poses an intractable problem for applications requiring real-time processing or control of ultrafast information systems. Here we break this barrier by proposing and experimentally demonstrating computing based on an end-to-end and all-optical recurrent neural network harnessing the ultrafast nature of linear and nonlinear optical operations while avoiding electronic operations. The all-optical computer realizes linear operations, nonlinear functions, and memory entirely in the optical domain with $>100~\mathrm{GHz}$ clock rates. We experimentally demonstrate a prototypical task of noisy waveform classification as well as perform ultrafast in-situ analysis of the soliton states from integrated optical microresonators. We further illustrate the application of the architecture for generative artificial intelligence based on quantum fluctuations to generate images even in the absence of input optical signals. Our results highlight the potential of all-optical computing beyond what can be achieved with digital electronics by utilizing ultrafast linear, nonlinear, and memory functions and quantum fluctuations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_05756 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | All-optical computing with beyond 100-GHz clock rates Li, Gordon H. Y. Parto, Midya Ge, Jinhao Ji, Qing-Xin Gao, Maodong Yu, Yan Williams, James Gray, Robert M. Leefmans, Christian R. Englebert, Nicolas Vahala, Kerry J. Marandi, Alireza Optics A computer's clock rate ultimately determines the minimum time between sequential operations or instructions. Despite exponential advances in electronic computer performance owing to Moore's Law and increasingly parallel system architectures, computer clock rates have remained stagnant at $\sim5~\mathrm{GHz}$ for almost two decades. This poses an intractable problem for applications requiring real-time processing or control of ultrafast information systems. Here we break this barrier by proposing and experimentally demonstrating computing based on an end-to-end and all-optical recurrent neural network harnessing the ultrafast nature of linear and nonlinear optical operations while avoiding electronic operations. The all-optical computer realizes linear operations, nonlinear functions, and memory entirely in the optical domain with $>100~\mathrm{GHz}$ clock rates. We experimentally demonstrate a prototypical task of noisy waveform classification as well as perform ultrafast in-situ analysis of the soliton states from integrated optical microresonators. We further illustrate the application of the architecture for generative artificial intelligence based on quantum fluctuations to generate images even in the absence of input optical signals. Our results highlight the potential of all-optical computing beyond what can be achieved with digital electronics by utilizing ultrafast linear, nonlinear, and memory functions and quantum fluctuations. |
| title | All-optical computing with beyond 100-GHz clock rates |
| topic | Optics |
| url | https://arxiv.org/abs/2501.05756 |