Integrated lithium niobate microwave photonic processing engine

• 成果类型: Article
• 署名作者: Feng, Hanke; Ge, Tong; Guo, Xiaoqing; Wang, Benshan; Zhang, Yiwen; Chen, Zhaoxi; Zhu, Sha; Zhang, Ke; Sun, Wenzhao; Huang, Chaoran; Yuan, Yixuan; Wang, Cheng
• 署名单位: City University of Hong Kong; City University of Hong Kong; University of Oxford; Chinese University of Hong Kong; Beijing University of Technology; City University of Hong Kong (Dongguan); Shenzhen Research Institute, City University of Hong Kong; City University of Hong Kong
• 刊物名称: Nature
• ISSN/ISSBN: 0028-5286
• DOI: 10.1038/s41586-024-07078-9
• 发表日期: 2024-03-07
• 页码: 80-+
• 关键词: chip; TECHNOLOGY; modulation; generation

摘要

Integrated microwave photonics (MWP) is an intriguing technology for the generation, transmission and manipulation of microwave signals in chip-scale optical systems(1,2). 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 filters(3-5), microwave signal processing(6-9) and image recognition(10,11). 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.