Research Area: Metaheuristic Computing
This paper proposes a novel wavefront-shaping-based focusing method, by introducing the differential evolution algorithm (DEA), thereby realising a faster convergence rate and improved enhancement compared to rival algorithms. Via simulations, we show that our proposed DEA-based approach delivers the best focusing performance irrespective of the influence of noise. Experimental results demonstrate that the DEA boosts the enhancement for an equivalent number of measurements compared with conventional optimisation methods. Furthermore, we reveal the influence of certain DEA parameters, leading to the emergence of many modified DEAs that perform impressively. The proposed DEA-based method simplifies the computational complexity and implementation process of wavefront shaping, offering useful insights for the future study of optimisation algorithms for wavefront shaping, as well as potential for practical applications, such as deep tissue focusing.
Keywords:
Global optimization
wavefront shaping
differential evolution algorithm
Author(s) Name: Yingzi Hua, Xiubao Sui, Shenghang Zhou, Qian Chen, Guohua Gu, Hongyang Bai, Wei Li
Journal name: Optics Communications
Conferrence name:
Publisher name: Elsevier
DOI: 10.1016/j.optcom.2020.126541
Volume Information: Volume 481, 15 February 2021, 126541
