Integrated lithium niobate microwave photonic processing engine
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , |
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| Format: | Preprint |
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2023
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| _version_ | 1866914631346290688 |
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| author | Feng, Hanke Ge, Tong Guo, Xiaoqing Wang, Benshan Zhang, Yiwen Chen, Zhaoxi Zhu, Sha Zhang, Ke Sun, Wenzhao Huang, Chaoran Yuan, Yixuan Wang, Cheng |
| author_facet | Feng, Hanke Ge, Tong Guo, Xiaoqing Wang, Benshan Zhang, Yiwen Chen, Zhaoxi Zhu, Sha Zhang, Ke Sun, Wenzhao Huang, Chaoran Yuan, Yixuan Wang, Cheng |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_14415 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Integrated lithium niobate microwave photonic processing engine Feng, Hanke Ge, Tong Guo, Xiaoqing Wang, Benshan Zhang, Yiwen Chen, Zhaoxi Zhu, Sha Zhang, Ke Sun, Wenzhao Huang, Chaoran Yuan, Yixuan Wang, Cheng Optics Applied Physics 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. |
| title | Integrated lithium niobate microwave photonic processing engine |
| topic | Optics Applied Physics |
| url | https://arxiv.org/abs/2306.14415 |