Machine learning-based classification of structured light modes under turbulence and eavesdropping effects DOI
Ahmed B. Ibrahim,

Faisal J. Aljasser,

Saud A. Alowais

и другие.

Applied Optics, Год журнала: 2024, Номер 63(16), С. 4405 - 4405

Опубликована: Май 8, 2024

This paper considers the classification of multiplexed structured light modes, aiming to bolster communication reliability and data transfer rates, particularly in challenging scenarios marked by turbulence potential eavesdropping. An experimental free-space optic (FSO) system is established transmit 16 modes [8-ary Laguerre Gaussian (LG) 8-ary superposition LG (Mux-LG) mode patterns] over a 3-m FSO channel, accounting for interception threats effects. To best authors' knowledge, this first consider both factors concurrently. We propose four machine/deep learning algorithms-artificial neural network, support vector machine, 1D convolutional 2D network-for purposes. By fusing outputs these methods, we achieve promising results exceeding 92%, 81%, 69% cases weak, moderate, strong turbulence, respectively. Structured exhibit significant variety real-world applications where reliable high-capacity transmission crucial.

Язык: Английский

Controlling auto-focusing chirped perfect Laguerre-Gaussian beam to mitigate crosstalk in atmospheric turbulence DOI
Yangbin Ma, Xinguang Wang, Yangbo Shen

и другие.

Optical and Quantum Electronics, Год журнала: 2025, Номер 57(4)

Опубликована: Апрель 3, 2025

Язык: Английский

Процитировано

0
Single-shot intensity-based measurement of high-order OAM in partially coherent vortex beams DOI Creative Commons
Zhao Zhang,

Yuanbo Wu,

Xin Liu

и другие.

Optics and Lasers in Engineering, Год журнала: 2025, Номер 193, С. 109085 - 109085

Опубликована: Май 16, 2025

Язык: Английский

Процитировано

0
Bessel beam propagation using radial beam propagation method at different propagation scales DOI Creative Commons
Adel Shaaban Awad Elsharkawi,

I-Chen Tsai,

Xiang-Ting Lin

и другие.

Optics Express, Год журнала: 2024, Номер 32(17), С. 30242 - 30242

Опубликована: Июль 19, 2024

This paper is devoted to studying the Bessel beam propagation in cylindrical coordinates using Hankel transform method (HT-BPM) and their behavior different scenarios microscale meter scale of distances. The study compares results obtained from HT-BPM with another fast Fourier (FFT-BPM) validate accuracy effectiveness modeling propagation. axial intensity analyzed HT-BPM. simulation are compared those FFT-BPM evaluate agreement consistency between two methods predicting show that numerically faster than by ten times for sampling points, furthermore, evaluating spot radius 89.9% analytical value, while 99% relative value. prediction has been tested at types phase functions distances: micrometer, centimeter, scales. matched experimental values. Finally, when input light source takes profiles.

Язык: Английский

Процитировано

2
Advances in artificial intelligence for artificial metamaterials DOI Creative Commons
Tosihide H. YOSIDA,

Rong Niu,

Chenyang Dang

и другие.

APL Materials, Год журнала: 2024, Номер 12(12)

Опубликована: Дек. 1, 2024

The 2024 Nobel Prizes in Physics and Chemistry were awarded for foundational discoveries inventions enabling machine learning through artificial neural networks. Artificial intelligence (AI) metamaterials are two cutting-edge technologies that have shown significant advancements applications various fields. AI, with its roots tracing back to Alan Turing’s seminal work, has undergone remarkable evolution over decades, key including the Turing Test, expert systems, deep learning, emergence of multimodal AI models. Electromagnetic wave control, critical scientific research industrial applications, been significantly broadened by metamaterials. This review explores synergistic integration metamaterials, emphasizing how accelerates design functionality materials, while novel physical networks constructed from enhance AI’s computational speed ability solve complex problems. paper provides a detailed discussion AI-based forward prediction inverse principles metamaterial design. It also examines potential big-data-driven methods addressing challenges In addition, this delves into role advancing focusing on progress electromagnetic optics, terahertz, microwaves. Emphasizing transformative impact intersection between underscores improvements efficiency, accuracy, applicability. collaborative development process opens new possibilities innovations photonics, communications, radars, sensing.

Язык: Английский

Процитировано

2
Machine learning-based classification of structured light modes under turbulence and eavesdropping effects DOI
Ahmed B. Ibrahim,

Faisal J. Aljasser,

Saud A. Alowais

и другие.

Applied Optics, Год журнала: 2024, Номер 63(16), С. 4405 - 4405

Опубликована: Май 8, 2024

This paper considers the classification of multiplexed structured light modes, aiming to bolster communication reliability and data transfer rates, particularly in challenging scenarios marked by turbulence potential eavesdropping. An experimental free-space optic (FSO) system is established transmit 16 modes [8-ary Laguerre Gaussian (LG) 8-ary superposition LG (Mux-LG) mode patterns] over a 3-m FSO channel, accounting for interception threats effects. To best authors' knowledge, this first consider both factors concurrently. We propose four machine/deep learning algorithms-artificial neural network, support vector machine, 1D convolutional 2D network-for purposes. By fusing outputs these methods, we achieve promising results exceeding 92%, 81%, 69% cases weak, moderate, strong turbulence, respectively. Structured exhibit significant variety real-world applications where reliable high-capacity transmission crucial.

Язык: Английский

Процитировано

0