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Photodetector Performance Prediction with Machine Learning

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Abstract

Four machine learning algorithms are tested to predict the performance metrics of modified uni-traveling carrier photodetectors from their design parameters. The highest accuracy (> 94%) is achieved with artificial neural networks.

© 2021 The Author(s)

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