Machine learning algorithms predict experimental output of chaotic lasers
Abstract
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Feb 14, 2023
- Source ID
- 10.1364/ol.483662
Entities
People
- M. Agüero
- M. Nonaka
- Marcelo G. Kovalsky
Organizations
- National Scientific and Technical Research Council
- Office of Naval Research Global