Abstract
We detail the implementation of an evolutionary optoelectronic feedback loop able to set ultrafast operation of a fiber laser cavity in specific dynamical regimes. In the present experimental realization, the tunable cavity parameters consist of the polarization states at two cavity locations, which are electrically controlled to shape the cavity nonlinear transfer function. After designing suitable merit functions, we show that distinct ultrafast dynamics can be obtained and discuss the challenges and potential of this advanced machine-learning strategy to target on-demand ultrafast dynamics.
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