Researchers in the US have created a photonic processor that provides programmable on-chip AI information processing without needing lithography.
The device developed at the University of Pennsylvania School of Engineering and Applied Science consists of spatially distributed optical gain and loss elements. Lasers cast light directly on a semiconductor wafer, without the need for defined lithographic pathways.
This uses dynamic control of spatial-temporal modulations of the imaginary index on an active semiconductor wafer. This tunes the optical gain distributions to route and switch optical signals to create neural networks. The processor has been tested with in situ training of vowel recognition with high accuracy.
“Photonic chips intended for machine learning applications face the obstacles of an intricate fabrication process where lithographic patterning is fixed, limited in reprogrammability, subject to error or damage and expensive,” said Liang Feng, Professor in the Departments of Materials Science and Engineering (MSE) and Electrical Systems and Engineering (ESE). “By removing the need for lithography, our chip overcomes those obstacles and offers improved accuracy and ultimate reconfigurability given the elimination of all kinds of constraints from predefined features.”
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