Inverse design of mode-locked fiber laser by improved genetic algorithm with classification algorithm - Kuang, Junxia; Zhang, Hong; Zhu, Yuehong; Chen, Rubo; Zhang, Gongruijian (Optics communications, 2026)
We propose an improved genetic algorithm assisted by a classification and recognition algorithm based on derivative analysis in mode-locked fiber lasers, which breaks through the limitation of traditional genetic algorithm that can only optimize a single objective at a time. By introducing the classification and recognition process of pulse and spectrum before fitness calculation, the design complexity of the fitness function is significantly reduced. The algorithm can also simultaneously search and optimize three types of targets: dissipative soliton, dispersion-managed soliton, and conventional soliton. Furthermore, a simple and flexible fitness function based on the net cavity dispersion has been constructed to achieve effective isolation with different types of solitons in the fitness space. Due to the structural advantages of this algorithm, each successfully recognized individual is retained, allowing to systematically study the dynamic behavior and pulse formation mechanism of lasers crossing the dispersion region under multi-parameter evolution. This research not only provides a new paradigm for the application of genetic algorithms in multi-objective optimization but also offers a controllable and scalable research framework for locking in the inverse-design parameters of the required mode-locked fiber laser.