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In Optics express

We propose a machine learning based approach to design few-mode DRAs by using neural networks to optimize the pump wavelengths, powers and mode content in order to obtain flat gain spectrum with low mode-dependent gain (MDG). Based on the proposed intelligent inverse design method, amplification optimization for the random fiber laser based two-mode DRA can be achieved with gain flatness of 1.0 dB and MDG of 0.6 dB at 14.5 dB on-off gain level. For backward pumping four-mode DRA, gain flatness of 0.46 dB and MDG of 0.3 dB can be achieved at 12.5 dB on-off gain.

Chen Yufeng, Du Jiangbing, Huang Yuting, Xu Ke, He Zuyuan