In the era of big data and artificial intelligence,optical neural networks(ONNs)have emerged as a promising alternative to conventional electronic approaches,offering superior parallelism,ultrafast processing speeds,a...In the era of big data and artificial intelligence,optical neural networks(ONNs)have emerged as a promising alternative to conventional electronic approaches,offering superior parallelism,ultrafast processing speeds,and high energy efficiency[1-3].However,a major bottleneck in the practical implementation of ONNs is the absence of effective nonlinear activation functions.Self-driven photodetectors have emerged as versatile optical to electrical converters,opening innovative avenues for energy-effective and flexibly integrated activation functions in ONNs through their reconfigurable optoelectronic nonlinearity.展开更多
基金supported by the National Natural Science Foundation of China(52422107,T2394471,and 62571319)Beijing Nova Program(20240484531)+1 种基金China Postdoctoral Science Foundation(2022M710074)and Open Research Fund Program of Beijing National Research Center for Information Science and Technology(04410304023).
文摘In the era of big data and artificial intelligence,optical neural networks(ONNs)have emerged as a promising alternative to conventional electronic approaches,offering superior parallelism,ultrafast processing speeds,and high energy efficiency[1-3].However,a major bottleneck in the practical implementation of ONNs is the absence of effective nonlinear activation functions.Self-driven photodetectors have emerged as versatile optical to electrical converters,opening innovative avenues for energy-effective and flexibly integrated activation functions in ONNs through their reconfigurable optoelectronic nonlinearity.
