Predicting frequency comb structure in nonlinear optical fibre using a neural network

We deploy a neural network to predict the spectro-temporal evolution of simple sinusoidal temporal modulations upon propagation in a nonlinear dispersive fibre. Thanks to the speed of the neural network, we can efficiently scan the input parameter space for the generation of on-demand frequency combs or the occurrence of substantial spectral/temporal focusing.