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Physics-informed Neural Network for Forecasting Time-domain Signals in Terahertz Resonances

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Abstract

We present a physics-informed recurrent neural network to precisely forecast long time-domain signals from a wide range of terahertz resonance features using short input signals. This can accelerate the discovery of new physical phenomena.

© 2022 The Author(s)

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