Universal and Improved Mutation Strategy for Feedback-based Wavefront Shaping Optimization Algorithm

When light passes through scattering media,such as biological tissues and multimode fibers,the wavefront of the beam is disturbed due to multiple scattering and distortion. This phenomenon is usually seen as an obstacle to biomedical imaging,telecommunications,and photodynamic therapy. As an effective method,iterative wavefront shaping is capable of manipulating the incident wavefront and compensating the wavefront distortion due to multiple scattering. Recent advances in iterative wavefront shaping techniques have made it possible to manipulate the light focusing and transport in scattering media. To improve the optimization performance,various optimization algorithms and improved strategies have been utilized. However,an improved strategy that is suitable for various algorithms has not been demonstrated yet. Here,a novel guided mutation strategy is proposed to improve optimization efficiency for light focusing through scattering medium. Not limited to a specific algorithm,guided mutation strategy is extended to various feedback- based wavefront shaping algorithms. In this study, single point focusing is firstly conducted in a feedback wavefront shaping system based on multiple classical optimization algorithms, including genetic algorithm, particle swarm algorithm, ant colony algorithm and simulated annealing algorithm. To validate the effectiveness of the guided mutation strategy in improving the focusing efficiency, the guided mutation strategy is introduced on the basis of the above four algorithms. The focusing efficiency is characterized by the enhancement factor after optimization and the number of iteration cycles when the maximum enhancement factor is reached as made by regular algorithms. Through numerical simulation and experimental verification, the guided mutation strategy greatly improves the focusing efficiency of the four classical optimization algorithms. The enhancement factor increases by more than 25%,the number of iteration cycles is reduced by more than 63%. When the input modes numbers increases,the benefits of the guided mutation strategy will become more significant. To further verify the universality of the guided mutation strategy,numerical simulation analysis of single point focusing with binary modulation and multi-point focusing with multi-objective genetic algorithm are also carried out. The results show that,similar to the single point focusing with phase modulation,the guided mutation strategy can effectively enhance the focusing efficiency with binary modulation and multi- objective optimization. This investigation of binary and multi-objective optimization further demonstrate that guided mutation strategy can be applied to widely applications,such as binary amplitude optimization system and multipoint uniform focusing. Overall,this study provides a more efficient focusing strategy for various classical algorithms and regulation methods of feedback wavefront shaping. For both phase modulation and binary amplitude modulation,considerable improvements in optimization effect and rate have been obtained with the introduce of guided mutation strategy. Because of the effectiveness and universality of the guided mutation strategy,it will be beneficial for applications ranging from controlling the transmission of light through disordered media to optical manipulation behind them. And this research will have potential application value in the field of fiber laser,two- photon microscopy and optogenetics.