期刊
OPTICAL FIBER TECHNOLOGY
卷 45, 期 -, 页码 306-312出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.yofte.2018.08.007
关键词
Nonlinear shaping; Machine learning; Nonlinear fiber optics
资金
- Institut Universitaire de France (IUF)
- Agence Nationale de la Recherche (Labex ACTION program) [ANR-11-LABX-01-01]
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.
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