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Nanostructured Photonic Power Splitter Design via Convolutional Neural Networks

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Abstract

We train a convolutional neural network (CNN) that can predict the optical response of randomly generated nanopatterned photonic power splitters in a 2400 design space with a prediction correlation coefficient of 85 %.

© 2019 The Author(s)

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