Machine learning algorithms predict experimental output of chaotic lasers

NONAKA, M.; AGÜERO, M.; KOVALSKY, M.

OPTICS LETTERS

OPTICAL SOC AMER

Año: 2023 vol. 48 p. 1060 - 1063

0146-9592

We apply an artificial neural network (ANN) of 20 hidden layers and backpropagation regression to the forecast of experimental time series from a Kerr lens mode locking (KLM) Ti:sapphire laser and a Nd:vanadate with modulation losses. In both cases the neural network is able to predict up to 10 steps ahead. In the Ti:sapphire laser the prediction in pulse amplitude is accurate even when the pulse is an extreme event. In the Nd:vanadate laser we forecast both pulse amplitude and pulse-to-pulse time separation. In both cases the prediction goes beyond the Lyapunov prediction horizon.