Wavefront Reconstruction for a Holographic Modal Wavefront Sensor Based on Extreme Learning Machine

IF 2.1 4区工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Photonics Journal Pub Date : 2025-02-17 DOI:10.1109/JPHOT.2025.3542831

Han Cao;Kainan Yao;Jianli Wang;Minglu Li;Leqiang Yang;Zhiqiang Xu

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引用次数: 0

Abstract

The intermodal crosstalk effect as well as the limited dynamic range of holographic modal wavefront sensors (HMWFSs) significantly affect their wavefront-sensing accuracy. Thus, this study was aimed at proposing an extreme learning machine (ELM)-based wavefront-reconstruction algorithm for holographic HMWFSs to overcome the errors caused by crosstalk as well as extend the dynamic range of the sensors. The simulation results indicated that the proposed ELM-based algorithm reduced the crosstalk-induced residual wavefront root mean square error to 4.7% of the initial value, and this was 84.6% lower than the reduction achieved by the conventional sensitivity-matrix method. After selecting the optimal range of training samples, the ELM model further reduced the residual error by approximately 74% under aberration conditions, where the conventional method reached its convergence limit. Thus, we proposed an ELM model for mitigating the issue of the linear regression relationship between the differential signals measured by HMWFS and the incident-wavefront Zernike-mode coefficients under the aberration-mode crosstalk effect.

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基于极限学习机的全息模态波前传感器波前重构

模态波前传感器的多模态串扰效应和有限的动态范围严重影响了其波前传感精度。因此，本研究旨在提出一种基于极限学习机（ELM）的全息hmwfs波前重构算法，以克服串扰带来的误差，并扩展传感器的动态范围。仿真结果表明，基于elm的算法将串扰引起的残余波前均方根误差降低到初始值的4.7%，比传统灵敏度矩阵法降低了84.6%。在选择了训练样本的最优范围后，ELM模型进一步将像差条件下的残差降低了约74%，达到了传统方法的收敛极限。因此，我们提出了一个ELM模型，以缓解在像差模串扰效应下由HMWFS测量的差分信号与入射波前Zernike-mode系数之间的线性回归关系。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Photonics Journal ENGINEERING, ELECTRICAL & ELECTRONIC-OPTICS

CiteScore

4.50

自引率

8.30%

发文量

489

审稿时长

1.4 months

期刊介绍： Breakthroughs in the generation of light and in its control and utilization have given rise to the field of Photonics, a rapidly expanding area of science and technology with major technological and economic impact. Photonics integrates quantum electronics and optics to accelerate progress in the generation of novel photon sources and in their utilization in emerging applications at the micro and nano scales spanning from the far-infrared/THz to the x-ray region of the electromagnetic spectrum. IEEE Photonics Journal is an online-only journal dedicated to the rapid disclosure of top-quality peer-reviewed research at the forefront of all areas of photonics. Contributions addressing issues ranging from fundamental understanding to emerging technologies and applications are within the scope of the Journal. The Journal includes topics in: Photon sources from far infrared to X-rays, Photonics materials and engineered photonic structures, Integrated optics and optoelectronic, Ultrafast, attosecond, high field and short wavelength photonics, Biophotonics, including DNA photonics, Nanophotonics, Magnetophotonics, Fundamentals of light propagation and interaction; nonlinear effects, Optical data storage, Fiber optics and optical communications devices, systems, and technologies, Micro Opto Electro Mechanical Systems (MOEMS), Microwave photonics, Optical Sensors.