Focusing light into an arbitrary pattern through multimode fiber is highly desired in energy delivery-related biomedical applications and has been demonstrated feasible with wavefront shaping. Here, the strategy relying on natural gradient ascent-based parameter optimization is shown to search the optimal wavefront rapidly towards high-quality pattern projection through a multimode fiber. Meanwhile, a new fitness function based on cosine similarity is adopted to replace the commonly used Pearson correlation coefficient, which leads to higher pattern contrast without sacrificing the fidelity with the target. With the proposed scheme, long-distance projection of arbitrary pattern was demonstrated through a 15-meter unfixed multimode fiber, showing fast convergence and better anti-interference ability. The superior performance of our approach for generating arbitrary pattern may gains special interest in multimode fiber based deep-tissue photon therapy and optogenetics.
We propose a hybrid algorithm based on genetic algorithm (GA) and ant colony optimization (ACO) for optical focusing inside/through scattering media. The hybrid algorithm has the basic structure of a GA, where the offspring generation procedures (i.e., parent selection and crossover) are replaced by the path generation procedures in ACO. The GA-ACO is advantageous by the rapid discovery of good solutions from ACO and enhanced solution diversity from GA. Therefore, the algorithm has a strong ability to search for a global optimal solution quickly, and experimentally we can achieve optimization results approaching the theoretical optimum.
In this work, we proposed a parameter-free algorithm (PFA) for iterative wavefront shaping, in which the time-consuming parameter tuning process is not required. The simulation and experiment results show that PFA can achieve better performance than GA and BA, without a parameter tuning process. Furthermore, since the mutation rate in PFA is inherited from the dynamic mutation algorithm, which has demonstrated high adaptability against perturbations, the robustness of PFA is satisfactory. In the future, a field-programmable gate array (FPGA) based system can be implemented to accelerate iterative wavefront shaping and achieve real-time optical focusing in dynamic scattering media, such as biological tissue.
We introduce a novel feedback-based wavefront shaping algorithm “dynamic mutation algorithm (DMA)”, which has high adaptability and a unique recovery ability. The optimization is based on the real-time error rate, which implies how far the optimization has gone toward the theoretical optimal result. The phase map is dynamically mutated according to the instant optimization state. When it encounters alteration in the transmission matrix, the diminished focus can be recovered, which no other current algorithms can achieve as they are usually heavily based on previous iterative results. The new algorithm has the potential to boost many applications in unstable scattering environments.
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