Parameter-free optimization algorithm for iterative wavefront shaping
Qi Zhao†, Chi Man Woo†, Huanhao Li, Tianting Zhong, Zhipeng Yu, and Puxiang Lai
Zhipeng Yu* (Department of Biomedical Engineering, Hong Kong Polytechnic University) eric-zhipeng.yu@connect.polyu.hk
Puxiang Lai* (Department of Biomedical Engineering, Hong Kong Polytechnic University) puxiang.lai@polyu.edu.hk
Optical focusing through scattering media has a significant impact on optical applications in biological tissues. Recently, iterative wavefront shaping (WFS) has been successfully used to focus light through or inside scattering media, and various heuristic algorithms have been introduced to improve the performance. While these results are encouraging, more efforts are needed to tune parameters towards robust and optimum optimization. Moreover, optimal parameters might differ for different scattering samples and experimental conditions. In this Letter, we propose a “smart” parameter-free algorithm by combining a traditional genetic algorithm with a bat algorithm, and the mutation rate can be automatically calculated through real-time feedback. Using this method in iterative WFS, one can achieve robust and optimum performance without a parameter tuning process.
Fig. Flow charts of different optimization algorithms used in Wavefront Shaping: (a) Bat algorithm, (b) Genetic algorithm, and (c) Parameter-free algorithm.