Integrated lithium niobate microwave photonic processing engine

Hanke Feng, Tong Ge, Xiaoqing Guo, Benshan Wang, Yiwen Zhang, Zhaoxi Chen, Sha Zhu, Ke Zhang, Wenzhao Sun, Chaoran Huang, Yixuan Yuan and Cheng Wang ()
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Hanke Feng: City University of Hong Kong
Tong Ge: City University of Hong Kong
Xiaoqing Guo: City University of Hong Kong
Benshan Wang: Chinese University of Hong Kong
Yiwen Zhang: City University of Hong Kong
Zhaoxi Chen: City University of Hong Kong
Sha Zhu: City University of Hong Kong
Ke Zhang: City University of Hong Kong
Wenzhao Sun: City University of Hong Kong
Chaoran Huang: Chinese University of Hong Kong
Yixuan Yuan: City University of Hong Kong
Cheng Wang: City University of Hong Kong

Nature, 2024, vol. 627, issue 8002, 80-87

Abstract: Abstract Integrated microwave photonics (MWP) is an intriguing technology for the generation, transmission and manipulation of microwave signals in chip-scale optical systems1,2. In particular, ultrafast processing of analogue signals in the optical domain with high fidelity and low latency could enable a variety of applications such as MWP filters3–5, microwave signal processing6–9 and image recognition10,11. An ideal integrated MWP processing platform should have both an efficient and high-speed electro-optic modulation block to faithfully perform microwave–optic conversion at low power and also a low-loss functional photonic network to implement various signal-processing tasks. Moreover, large-scale, low-cost manufacturability is required to monolithically integrate the two building blocks on the same chip. Here we demonstrate such an integrated MWP processing engine based on a 4 inch wafer-scale thin-film lithium niobate platform. It can perform multipurpose tasks with processing bandwidths of up to 67 GHz at complementary metal–oxide–semiconductor (CMOS)-compatible voltages. We achieve ultrafast analogue computation, namely temporal integration and differentiation, at sampling rates of up to 256 giga samples per second, and deploy these functions to showcase three proof-of-concept applications: solving ordinary differential equations, generating ultra-wideband signals and detecting edges in images. We further leverage the image edge detector to realize a photonic-assisted image segmentation model that can effectively outline the boundaries of melanoma lesion in medical diagnostic images. Our ultrafast lithium niobate MWP engine could provide compact, low-latency and cost-effective solutions for future wireless communications, high-resolution radar and photonic artificial intelligence.

Date: 2024
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DOI: 10.1038/s41586-024-07078-9

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