Based on such techniques as clustering, sharing, crowding and elite replacement, a hybrid genetic algorithm (GA) is proposed. This GA can effectively solve the multimodal optimization including the global and local optima in the quasi-phase-matching (QPM) difference frequency generation (DFG). The conversion efficiency and bandwidth, based on QPM-DFG, are optimized by the matrix operator and hybrid GA. Optimized examples for five-, six- and seven-segment QPM gratings are given, respectively. The optimal results show that adding the segment number of QPM can obviously broaden the conversion bandwidth.
Fast and accurate methods for Raman amplifier propagation equations are proposed. Numerical results demonstrate that these methods can increase the accuracy by more than one or two orders of magnitude in comparison with the classical methods, and the computing speed can increase more than 16 times compared to the classical fourth-order Runge-Kutta method on the same conditions.