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- W3048367772 abstract "Formation of the Kerr soliton combs is a widely recognized important but complex issue, which relates to cross-influences among intra-cavity nonlinearities, chromatic dispersions, mode interactions, and pumping effects. Here, we propose and demonstrate a deep neural network model to predict Kerr comb spectra in silica microspheres statistically, via training their transmission spectra. Such a scheme enables soliton comb identification under a particular pump scanning, with error <; 8%, verified by experimental measurements. This study bridging the deep learning and the microcomb photonics, may provide a powerful and convenient tool for photonic device test and investigation." @default.
- W3048367772 created "2020-08-18" @default.
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- W3048367772 date "2020-12-01" @default.
- W3048367772 modified "2023-10-18" @default.
- W3048367772 title "Predicting Kerr Soliton Combs in Microresonators via Deep Neural Networks" @default.
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- W3048367772 doi "https://doi.org/10.1109/jlt.2020.3015586" @default.
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