All-optical machine learning using diffractive deep neural networks
Xing Lin, Yair Rivenson, Nezih T. Yardimci, Muhammed Veli, Yi Luo, Mona Jarrahi, Aydogan Ozcan
Science·2018·1907 citations
<jats:title>All-optical deep learning</jats:title><jats:p>Deep learning uses multilayered artificial neural networks to learn digitally from large datasets. It then performs advanced identification and classification tasks. To date, these multilayered neural networks have been implemented on a computer. Lin<jats:italic>et al.</jats:italic>demonstrate all-optical machine learning that uses passive optical components that can be patterned and fabricated with 3D-printing. Their hardware approach comprises stacked layers of diffractive optical elements analogous to an artificial neural network that can be trained to execute complex functions at the speed of light.</jats:p><jats:p><jats:italic>Science</jats:italic>, this issue p.<jats:related-article xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="doi" issue="6406" page="1004" related-article-type="in-this-issue" vol="361" xlink:href="10.1126/science.aat8084">1004</jats:related-article></jats:p>