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We report a framework comprising of a combination of sequence models (e.g. RNN, LSTM, Bi LSTM etc) and deep neural networks (DNNs) to tackle the forward problem of predicting the optical response for a given geometry of a broadband, terahertz metamaterial absorber based on Au split-ring resonators. We obtained a training and validation losses of 0.0062 and 0.0042 respectively. The test dataset for this model yielded a loss of 0.0026. Using our model, we were able to predict the spectral response of similar metamaterial absorber geometries in less than 0.5 seconds.
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