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Compact eternal diffractive neural network chip for extreme environments

Engineering and Technology

Compact eternal diffractive neural network chip for extreme environments

Y. Dong, D. Lin, et al.

Discover how Yibo Dong, Dajun Lin, Long Chen, Baoli Li, Xi Chen, Qiming Zhang, Haitao Luan, Xinyuan Fang, and Min Gu have revolutionized optical inference with their innovative millimeter-scale diffractive neural network chip, boasting an impressive 82% accuracy in handwritten digit recognition and unparalleled durability in extreme environments.

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Playback language: English
Abstract
This paper presents a millimeter-scale, robust bilayer-integrated diffractive neural network (DNN) chip for optical inference in extreme environments. The chip, fabricated by engraving two binary phase-modulated diffractive layers onto a quartz wafer, achieved 82% accuracy in handwritten digit recognition. Its high-temperature stability and estimated room-temperature lifetime of 1.84 × 10²³ trillion years make it suitable for extreme environment applications.
Publisher
Communications Engineering
Published On
May 01, 2024
Authors
Yibo Dong, Dajun Lin, Long Chen, Baoli Li, Xi Chen, Qiming Zhang, Haitao Luan, Xinyuan Fang, Min Gu
Tags
diffractive neural network
optical inference
high-temperature stability
millimeter-scale chip
handwritten digit recognition

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