Integrated lithium niobate microwave photonic processing engine

计算机科学 光子学 信号处理 电子工程 铌酸锂 计算机硬件 数字信号处理 光学 工程类 物理
作者
Hanke Feng,Tong Ge,Xiaoqing Guo,Wang, Benshan,Yiwen Zhang,Zhaoxi Chen,Sha Zhu,Ke Zhang,Wenzhao Sun,Huang, Chaoran,Yixuan Yuan,Cheng Wang
出处
期刊:Cornell University - arXiv [Cornell University]
被引量:4
标识
DOI:10.48550/arxiv.2306.14415
摘要

Integrated microwave photonics is an intriguing field that leverages integrated photonic technologies for the generation, transmission, and manipulation of microwave signals in chip-scale optical systems. In particular, ultrafast processing and computation of analog electronic signals in the optical domain with high fidelity and low latency could enable a variety of applications such as MWP filters, microwave signal processing, and image recognition. An ideal photonic platform for achieving these integrated MWP processing tasks shall simultaneously offer an efficient, linear and high-speed electro-optic modulation block to faithfully perform microwave-optic conversion at low power, and a low-loss functional photonic network that can be configured for a variety of signal processing tasks, as well as large-scale, low-cost manufacturability to monolithically integrate the two building blocks on the same chip. In this work, we demonstrate such an integrated MWP processing engine based on a thin-film lithium niobate platform capable of performing multi-purpose processing and computation tasks of analog signals up to 92 giga samples per second at CMOS-compatible voltages. We demonstrate high-speed analog computation, i.e., first- and second-order temporal integration and differentiation with computing accuracies up to 98.1 %, and deploy these functions to showcase three proof-of-concept applications, namely, ordinary differential equation solving, ultra-wideband signal generation and high-speed edge detection of images. We further leverage the image edge detector to enable a photonic-assisted image segmentation model that could effectively outline the boundaries of melanoma lesion in medical diagnostic images, achieving orders of magnitude faster processing speed and lower power consumption than conventional electronic processors.
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