Backscattered light field control based on self-adaptive genetic algorithm

DUAN Meigang; ZHANG Chenlong; ZHAO Ying; WANG Jianmin; ZUO Haoyi

doi:10.7498/aps.74.20250455

Abstract

Modulating the light field scattered by scattering media has potential applications in biological tissue imaging, military anti-terrorism, and optical information transmission. However, light reflected by complex scattering media, such as biological tissues, clouds and fog, multi-mode fiber, and white paper, will produce disorderly scattering, and then disturb the wavefront of incident light. It has always been the main obstacle to optical imaging and effective information transmission. Therefore, the control of backscattered light field is also a research field worthy of attention, which is of great significance for the transmission of non-line-of-sight optical information. It is also very important to find a method of efficiently controlling backscattered light field for the breakthrough of related applications. It has been found that iterative wavefront shaping technology is an effective solution, which gradually modulates the amplitude or phase distribution of wavefront according to the feedback of the light intensity distribution in the target area of charge coupled device (CCD). An improved genetic algorithm, self-adaptation genetic algorithm (SAGA), is proposed, which can be used to rapidly modulate the backscattered light field. The amplitude distribution of wavefront is controlled, which makes it form the required pattern at the target position through the interference of light. During the implementation of the algorithm, the SAGA performs gene crossover and mutation separately, and selects gene crossover and mutation operations according to the number of iterations. At the beginning of evolution, the probability of selecting gene mutations is higher because the population needs to adapt to the environment, while at the end of evolution, the probability of selecting gene mutations is lower because it gradually adapts to the environment. In the experimental measurement, the effective modulation area of digital-micromirror device (DMD) is 1024×1024, which is divided into 64×64 modulation segments by pixel merging. Each segment number is assigned a value of 0 or 1. Focusing and image projection performance of scattered light field are evaluated based on peak-to-background ratio (PBR) and Pearson correlation coefficient (Cor), respectively. By comparing the scattered light focusing and image projection of SAGA and genetic algorithm (GA), it is found that SAGA can accurately control the backscattered light field and converge to the optimal value in a few iterations. After 1000 iterations, the GA still has a clear speckle background. With the increase of iteration times, GA will also show bright focus and clear projection image. Compared with GA, SAGA has a modulation speed that is 8.3 times faster in light focusing and 14.38 times faster in image projection, greatly improving the modulation speed of the scattered light field. The fast control technology for scattered light field can lead to numerous new optical communication applications and offer fresh insights into the study of optics and information science.

Keywords:

Authors and contacts

1.
School of Applied Sciences, Taiyuan University of Science and Technology, Taiyuan 030024, China
2.
College of Physics, Sichuan University, Chengdu 610065, China

Corresponding author: DUAN Meigang, duanmg.sxu@foxmail.com ; ZUO Haoyi, zuohaoyi@scu.edu.cn

Funds: Project supported by the National Natural Science Foundation of China (Grant No. 62475176), the Fundamental Research Program of Shanxi Province, China (Grant No. 202403021212259), the Science and Technology Innovation Plan of Colleges and Universities in Shanxi Province, China (Grant No. 2024L215), and the Project of Award Fund for Excellent Doctoral Work in Shanxi Province, China (Grant No. 20242077).

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References

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Cited By

图 1 背向散射光场调控原理图　(a)经散射介质反射的光场分布; (b)调制后的反射光场分布; (c) SAGA散射波前整形流程图

Figure 1. Schematics of modulation of backscattering field: (a) Distribution of light field reflected by scattering medium; (b) distribution of the reflected light field after modulation; (c) flowchart of SAGA.

DownLoad: Full-Size Img PowerPoint

图 2 实验装置图

Figure 2. Experimental setup.

DownLoad: Full-Size Img PowerPoint

图 3 SAGA和GA的背向散射聚焦实验结果　(a)迭代过程中的最佳聚焦模式; (b) 1000次迭代SAGA和GA的PBR值随迭代次数的变化; (c) 3000次迭代GA的PBR值随迭代次数的变化

Figure 3. Experimental results of backscatter focusing: (a) Optimal focusing mode in iterative process; (b) variation curve of PBR of SAGA and GA with 1000 iteration times; (c) variation curve of PBR of GA with 3000 iteration times.

DownLoad: Full-Size Img PowerPoint

图 4 SAGA和GA的图像投影实验结果　(a)目标图像; (b) SAGA在1000次迭代过程中的最佳投影结果; (c) GA在1000次迭代过程中的最佳投影结果; (d) GA在5000次迭代过程中的最佳投影结果; (e) 1000次迭代SAGA和GA的Cor值随迭代次数的变化; (f) 5000次迭代GA的Cor值随迭代次数的变化

Figure 4. Experimental results of image projection: (a) Target images; (b) the optimal image projection of SAGA with 1000 iteration times; (c) the optimal image projection of GA with 1000 iteration times; (d) the optimal image projection of GA with 3000 iteration times; (e) variation curve of Cor of SAGA and GA with 1000 iteration times; (f) variation curve of Cor of GA with 5000 iteration times.

DownLoad: Full-Size Img PowerPoint

[1]	Yaqoob Z, Psaltis D, Feld M S, Yang C 2008 Nat. Photonics 2 110 Google Scholar
[2]	Ni F, Liu H, Zheng Y, Chen X 2023 Adv. Photonics 5 046010
[3]	Bian Y, Wang F, Wang Y, Fu Z, Liu H, Yuan H, Situ G 2024 Photonics Res. 12 134 Google Scholar
[4]	段美刚, 赵映, 左浩毅 2024 物理学报 73 124203 Google Scholar Duan M G, Zhao Y, Zuo H Y 2024 Acta Phys. Sin. 73 124203 Google Scholar
[5]	Zhang X, Gao J, Gan Y, Song C, Zhang D, Zhuang S, Han S, Lai P, Liu H 2023 PhotoniX 4 10 Google Scholar
[6]	Mclntosh R, Goetschy A, Bender N, Yamilov A, Hsu C, Yılmaz H, Cao H 2024 Nat. Photonics 18 744 Google Scholar
[7]	Wu C, Liu J, Huang X, Li Z P, Yu C, Ye J T, Zhang J, Zhang Q, Dou X, Goyal V K, Xu F, Pan J W 2021 Nat. Photonics 118 e2024468118
[8]	孙雪莹, 刘飞, 段景博, 牛耕田, 邵晓鹏 2021 物理学报 70 224203 Google Scholar Sun X Y, Liu F, Duan J B, Niu G T, Shao X P 2021 Acta Phys. Sin. 70 224203 Google Scholar
[9]	张熙程, 方龙杰, 庞霖 2018 物理学报 67 104202 Google Scholar Zhang X C, Fang L J, Pang L 2018 Acta Phys. Sin. 67 104202 Google Scholar
[10]	Ding C, Shao R, Qu Y, He Q, Liu L, Yang J 2023 Laser Photonics Rev. 17 2300104 Google Scholar
[11]	相萌, 何飘, 王天宇, 袁琳, 邓凯, 刘飞, 邵晓鹏 2024 物理学报 73 124202 Google Scholar Xiang M, He P, Wang T Y, Yuan L, Deng K, Liu F, Shao X P 2024 Acta Phys. Sin. 73 124202 Google Scholar
[12]	Shi A D, Wang Z Y, Duan C X, Wang Z, Zhang W L 2024 Chin. Phys. B 33 104202 Google Scholar
[13]	沈乐成, 罗嘉伟, 张志凌, 张诗按 2024 光学学报 44 1026016 Google Scholar Shen Y C, Luo J W, Zhang Z L, Zhang S A 2024 Acta Opt. Sin. 44 1026016 Google Scholar
[14]	朱磊, 邵晓鹏 2020 光学学报 40 0111005 Google Scholar Zhu L, Shao X P 2020 Acta Opt. Sin. 40 0111005 Google Scholar
[15]	Cao Z Z, Zhang X B, Osnabrugge G, Li J H, Vellekoop I M, Koonen A M 2019 Light-Sci. Appl. 8 69 Google Scholar
[16]	Tzang O, Caravaca-Aguirre A M, Wagner K, Piestun R 2018 Nat. Photonics 12 368 Google Scholar
[17]	Teğin U, Rahmani B, Kakkava E, Borhani N, Moser C, Psaltis D 2020 APL Photonics 5 030804 Google Scholar
[18]	Qiao Y Q, Peng Y J, Zheng Y L, Ye F, Chen X 2018 Opt. Lett. 43 787 Google Scholar
[19]	倪枫超, 刘海港, 陈险峰 2024 光学学报 44 1026006 Google Scholar Ni F C, Liu H G, Chen X F 2024 Acta Opt. Sin. 44 1026006 Google Scholar
[20]	Vellekoop I M, Mosk A P 2007 Opt. Lett. 32 2309 Google Scholar
[21]	Liu J, Feng Y, Li W, Xiang M, Xi T, Liu F, Li G, Shao X 2023 Opt. Lett. 48 4077 Google Scholar
[22]	Wan L, Chen Z, Huang H, Pu J 2016 Appl. Phys. B 122 204
[23]	Peng T, Li R, An S, Yu X, Zhou M, Bai C, Liang Y, Lei M, Zhang G, Yao B, Zhang P 2019 Opt. Express 27 4858 Google Scholar
[24]	Yang J, He Q, Liu L, Qu Y, Shao R, Song B, Zhao Y 2021 Light- Sci. Appl. 10 149 Google Scholar
[25]	Wang X, Zhao W, Zhai A, Wang D 2023 Opt. Express 31 32287 Google Scholar
[26]	Zhang C, Yao Z, Liu T, Sui X, Chen Q, Xie Z, Liu G 2024 Opt. Laser Technol. 169 110018 Google Scholar
[27]	Woo C M, Zhao Q, Zhong T, Li H, Yu Z, Lai P 2022 APL Photonics 7 046109 Google Scholar
[28]	Li W, He W, Dai Y, Zuo H, Pang L 2024 Opt. Laser Technol. 175 110740 Google Scholar
[29]	Zhao Y, He Q, Li S, Yang J 2021 Opt. Lett. 46 1518 Google Scholar
[30]	Li H H, Woo C M, Zhong T T, Yu Z P, Luo Y Q, Zheng Y J, Yang X, Hui H, Lai P X 2021 Photonics Res. 9 202 Google Scholar
[31]	Yu H, Yao Z Y, Sui X B, Gu G H, Chen Q 2022 Optik 261 169129 Google Scholar
[32]	Deb K, Beyer H G 2001 Evol. Comput. 9 197 Google Scholar
[33]	Kivijärvi J, Fränti P, Nevalainen O 2003 J. Heuristics 9 113 Google Scholar
[34]	Hinterding R, Michalewicz Z, Peachey T C 1996 International Conference on Evolutionary Computation—The 4th International Conference on Parallel Problem Solving from Nature, Berlin Germany, September 22–26, 1996 pp420–429

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