Simultaneous temporal and spectral evolution of ultrafast optical pulse propagation using a single bidirectional LSTM network

Abstract

Numerical simulations of optical pulse evolution are often a cumbersome task, mostly due to the presence of nonlinearities, and standard numerical approaches like splitting methods can be too complex and resource-hungry to compute them. However, under certain conditions, deep learning (DL) techniques can provide accurate alternative approaches to predict such propagation behavior. Here, we show a bidirectional long short-term memory (BiLSTM) network that predicts both temporal and spectral evolution of a short optical pulse going through a 13 m highly nonlinear fiber (HNLF). The BiLSTM performed an RMSE metric of 0.004 and 0.012 for temporal and spectral domains, respectively. A supercontinuum generation was also performed in a 20-cm photonic-crystal fiber, and the BiLSTM returns an RMSE metric of 0.018 and 0.013 for temporal and spectral domains, respectively.