Nonlinear sculpturing of optical pulses with normally dispersive fiber-based devices

Christophe Finot, Ilya Gukov, Kamal Hammani, Sonia Boscolo

Research output: Contribution to journalArticlepeer-review


We present a general method to determine the parameters of nonlinear pulse shaping systems based on pulse propagation in a normally dispersive fiber that are required to achieve the generation of pulses with various specified temporal properties. The nonlinear shaping process is reduced to a numerical optimization problem over a three-dimensional space, where the intersections of different surfaces provide the means to quickly identify the sets of parameters of interest. We also show that the implementation of a machine-learning strategy can efficiently address the multi-parameter optimization problem being studied.
Original languageEnglish
Pages (from-to)306-312
JournalOptical Fiber Technology
Early online date23 Aug 2018
Publication statusPublished - Nov 2018


  • Nonlinear shaping, Machine learning, Nonlinear fiber optics


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