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Related Experiment Video

Updated: Aug 15, 2025

Fabrication and Testing of Photonic Thermometers

Fabrication and Testing of Photonic Thermometers

Published on: October 24, 2018

Microcomb-based integrated photonic processing unit.

Bowen Bai¹, Qipeng Yang¹, Haowen Shu¹

¹State Key Laboratory of Advanced Optical Communications System and Networks, School of Electronics, Peking University, Beijing, 100871, China.

Nature Communications

|January 5, 2023

Summary

This summary is machine-generated.

This study introduces a novel chip-based photonic processing unit (PPU) for optical neural networks (ONN). The PPU achieves high compute density and precision, enabling advanced artificial intelligence tasks.

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Last Updated: Aug 15, 2025

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Area of Science:

Photonics
Optical Computing
Artificial Intelligence Hardware

Background:

Optical neural networks (ONN) leverage optical wavelength for enhanced complexity and functionality.
Challenges remain in integrating ONN architectures for on-chip operations.

Purpose of the Study:

To implement a chip-based photonic processing unit (PPU) using a time-wavelength plane stretching approach for convolution operations.
To develop a control protocol enabling high weight precision for the PPU.

Main Methods:

Convolution operations implemented on a microcomb-driven chip-based PPU.
Development of a dedicated control and operation protocol.
Demonstration of image edge detection and handwritten digit recognition.

Main Results:

Achieved a record high weight precision of 9 bits.
Demonstrated a photonic-core compute density exceeding 1 trillion operations per second per square millimeter (TOPS mm⁻²).
Proof-of-concept experiments showed comparable processing capabilities to digital computers.

Conclusions:

The developed PPU offers advanced performance and scalability for sophisticated AI tasks.
Potential applications include autonomous driving, video action recognition, and image reconstruction.
This technology could revolutionize complex artificial intelligence applications.