Abstract
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 language | English |
|---|---|
| Pages (from-to) | 306-312 |
| Journal | Optical Fiber Technology |
| Volume | 45 |
| Early online date | 23 Aug 2018 |
| DOIs | |
| Publication status | Published - Nov 2018 |
Keywords
- Nonlinear shaping, Machine learning, Nonlinear fiber optics
Fingerprint
Dive into the research topics of 'Nonlinear sculpturing of optical pulses with normally dispersive fiber-based devices'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver