Researchers have developed an easy-to-use optical chip that can configure itself to achieve various functions. The positive real-valued matrix computation they have achieved gives the chip the potential to be used in applications requiring optical neural networks.
Optical neural networks can be used for a variety of data-heavy tasks such as image classification, gesture interpretation and speech recognition.
"Our new chip can be treated as a black box, meaning users don't need to understand its internal structure to change its function," said research team leader Jianji Dong from Huazhong University of Science and Technology in China."They only need to set a training objective, and, with computer control, the chip will self-configure to achieve the desired functionality based on the input and output.
They also demonstrated optical routing -- a specialized case of positive real matrix computation -- with a high extinction ratio. Optical routing can efficiently route optical signals between equipment, such as processors and memory units, in data centers. Compared to electrical counterparts, optical approaches help reduce latency and power consumption when processing a large number of signals.
The researchers are now working to make improvements to the chip that would allow even more matrix operation capabilities. They would also like to explore using it for other applications of matrix computing beyond optical neural networks.Researchers have shown that dissipative Kerr solitons can be used to create chip-based optical frequency combs with enough output power for use in optical atomic clocks and other practical ...
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