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Nanoprinted high-neuron-density optical linear perceptrons performing near-infrared inference on a CMOS chip

Engineering and Technology

Nanoprinted high-neuron-density optical linear perceptrons performing near-infrared inference on a CMOS chip

E. Goi, X. Chen, et al.

Discover the groundbreaking research on single-layer nanoscale holographic perceptrons conducted by Elena Goi, Xi Chen, Qiming Zhang, Benjamin P. Cumming, Steffen Schoenhardt, Haitao Luan, and Min Gu. These innovative devices, capable of exceeding 500 million neurons per square centimeter, hold remarkable potential in optical data processing and applications in decryption and medical diagnostics.

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Playback language: English
Abstract
This work presents single-layer nanoscale holographic perceptrons, nanoprinted on CMOS chips, for optical data processing. These devices, trained to perform optical inference tasks like decryption, achieve a neuron density exceeding 500 million neurons per square centimeter. Their near-infrared operation and power efficiency demonstrate potential for applications in optical decryption, sensing, medical diagnostics, and computing.
Publisher
Light: Science & Applications
Published On
Jan 31, 2021
Authors
Elena Goi, Xi Chen, Qiming Zhang, Benjamin P. Cumming, Steffen Schoenhardt, Haitao Luan, Min Gu
Tags
holographic perceptrons
optical data processing
neuron density
decryption
nanoprinted
CMOS chips
medical diagnostics

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