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Updated: Jul 2, 2025

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Integrated lithium niobate microwave photonic processing engine.

Hanke Feng1, Tong Ge1, Xiaoqing Guo1,2

  • 1Department of Electrical Engineering & State Key Laboratory of Terahertz and Millimeter Waves, City University of Hong Kong, Kowloon, China.

Nature
|February 28, 2024
PubMed
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This summary is machine-generated.

We developed an integrated microwave photonics (MWP) engine on thin-film lithium niobate for ultrafast analogue signal processing. This chip-scale platform enables high-speed computations and diverse applications in communications and AI.

Area of Science:

  • Photonics
  • Microwave Engineering
  • Materials Science

Background:

  • Integrated microwave photonics (MWP) offers chip-scale solutions for microwave signal generation, transmission, and manipulation.
  • Ultrafast analogue signal processing in the optical domain is crucial for applications like MWP filters, signal processing, and image recognition.
  • An ideal MWP platform requires efficient electro-optic modulation and low-loss photonic networks, with scalable manufacturing for monolithic integration.

Purpose of the Study:

  • To demonstrate an integrated MWP processing engine on a wafer-scale thin-film lithium niobate platform.
  • To achieve ultrafast analogue computation (integration and differentiation) at high sampling rates.
  • To showcase the platform's versatility through applications in solving differential equations, generating signals, and image processing.

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Main Methods:

  • Utilized a 4-inch wafer-scale thin-film lithium niobate platform for monolithic integration.
  • Implemented multipurpose processing tasks with bandwidths up to 67 GHz at CMOS-compatible voltages.
  • Achieved temporal integration and differentiation at sampling rates up to 256 giga samples per second.

Main Results:

  • Demonstrated ultrafast analogue computation capabilities, including temporal integration and differentiation.
  • Successfully applied these functions to solve ordinary differential equations, generate ultra-wideband signals, and detect image edges.
  • Developed a photonic-assisted image segmentation model for medical imaging, effectively outlining melanoma lesion boundaries.

Conclusions:

  • The developed thin-film lithium niobate MWP engine provides a compact, low-latency, and cost-effective solution.
  • This platform enables high-fidelity, high-speed analogue signal processing for advanced applications.
  • Potential impact on future wireless communications, high-resolution radar, and photonic artificial intelligence systems.