IEEE Photonics Technology Letters最新文献_第3页

A 28-nm CMOS EML Driver for 50G-PON Applications 50G-PON应用的28纳米CMOS EML驱动

IF 2.3 3区工程技术

IEEE Photonics Technology Letters Pub Date : 2025-06-24 DOI: 10.1109/LPT.2025.3582785

Ruixuan Yang;Yiming Dang;Yifei Xia;Cailing Li;Donghe Tu;Zhiyong Li;Li Geng;Dan Li

引用次数: 0

Fabrication and Optical Characterization of Low-Loss Barium Titanate Waveguides 低损耗钛酸钡波导的制备与光学特性

IF 2.3 3区工程技术

IEEE Photonics Technology Letters Pub Date : 2025-06-24 DOI: 10.1109/LPT.2025.3582846

M Ifaz Ahmad Isti;Xiaofeng Zhu;Marco Tulio Moller de Freitas;Peng Yao;Mohammad Jobayer Hossain;Shouyuan Shi;Garrett Schneider;Dennis W. Prather

引用次数: 0

Broadband Frequency-Hopping Radar With Fourier Domain Mode-Locking Period-One Laser Dynamics 傅立叶域锁模周期一激光动力学宽带跳频雷达

IF 2.3 3区工程技术

IEEE Photonics Technology Letters Pub Date : 2025-06-24 DOI: 10.1109/LPT.2025.3582759

Xiaoyue Yu;Fangzheng Zhang;Qing Xiong;Xin Yan;Yansen He;Gong Zhang;Shilong Pan;Yuan Yu

{"title":"Broadband Frequency-Hopping Radar With Fourier Domain Mode-Locking Period-One Laser Dynamics","authors":"Xiaoyue Yu;Fangzheng Zhang;Qing Xiong;Xin Yan;Yansen He;Gong Zhang;Shilong Pan;Yuan Yu","doi":"10.1109/LPT.2025.3582759","DOIUrl":"https://doi.org/10.1109/LPT.2025.3582759","url":null,"abstract":"A frequency hopping (FH) radar based on period-one oscillation laser dynamics with Fourier domain mode-locking (FDML) is proposed and experimentally demonstrated. In the transmitter, a broadband FH signal is generated by adjusting injection strength through intensity modulation. By further incorporating an optoelectronic feedback loop with the temporal period of the FH signal matched with its round-trip delay, the frequency stability and accuracy are greatly improved. In the receiver, to reduce the sampling rate and computational complexity, self-referenced frequency down conversion is applied and a kernel function correlation algorithm is adopted in digital signal processing to procure the high-resolution range profile. In the experiment, an FH signal with a bandwidth of 8 GHz is generated, based on which the detections of single-target and two-targets are demonstrated respectively, achieving a range resolution of 2.15 cm. The proposed photonics-based FH radar with FDML-based P1 dynamics for signal generation is supposed to find more applications in further high-resolution radar detection and imaging.","PeriodicalId":13065,"journal":{"name":"IEEE Photonics Technology Letters","volume":"37 19","pages":"1105-1108"},"PeriodicalIF":2.3,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Heterogeneously Integrated III-V/Silicon C-Band Tunable Lasers on 300-mm Silicon Photonic Wafers 在300毫米硅光子晶片上异质集成III-V/硅c波段可调谐激光器

IF 2.3 3区工程技术

IEEE Photonics Technology Letters Pub Date : 2025-06-23 DOI: 10.1109/LPT.2025.3581932

Guan-Lin Su;Ranjeet Kumar;Duanni Huang;David Gold;Richard Jones;Haisheng Rong

引用次数: 0

Broadband Absorption and Switchable Multiband Polarization Conversion via Graphene-VO2 Metasurface 基于石墨烯- vo2超表面的宽带吸收和可切换多波段偏振转换

IF 2.3 3区工程技术

IEEE Photonics Technology Letters Pub Date : 2025-06-19 DOI: 10.1109/LPT.2025.3581323

Shuo Zhang;Yazheng Hao;Guotai Liu;Rui Yang

引用次数: 0

Implementation of 105 m Dynamic Underwater Wireless Optical Communication in the Deep Sea 105米动态水下无线光通信在深海中的实现

IF 2.3 3区工程技术

IEEE Photonics Technology Letters Pub Date : 2025-06-18 DOI: 10.1109/LPT.2025.3580742

Tingwei Fan;Tianhua Zhou;Guyu Hu;Hanbin Gu

引用次数: 0

End-to-End Learning of Probabilistic Constellation Shaping Through Importance Sampling 基于重要性抽样的概率星座形成的端到端学习

IF 2.3 3区工程技术

IEEE Photonics Technology Letters Pub Date : 2025-06-18 DOI: 10.1109/LPT.2025.3580672

Shrinivas Chimmalgi;Laurent Schmalen;Vahid Aref

{"title":"End-to-End Learning of Probabilistic Constellation Shaping Through Importance Sampling","authors":"Shrinivas Chimmalgi;Laurent Schmalen;Vahid Aref","doi":"10.1109/LPT.2025.3580672","DOIUrl":"https://doi.org/10.1109/LPT.2025.3580672","url":null,"abstract":"Probabilistic constellation shaping enables easy rate adaption and has been proven to reduce the gap to Shannon capacity. Constellation point probabilities are optimized to maximize either the mutual information or the bit-wise mutual information. The optimization problem is however challenging even for simple channel models. While autoencoder-based machine learning has been applied successfully to solve this problem, it requires manual computation of additional terms for the gradient which is an error-prone task. In this work, we present novel loss functions for autoencoder-based learning of probabilistic constellation shaping for coded modulation systems using automatic differentiation and importance sampling. We show analytically that our proposed approach also uses exact gradients of the constellation point probabilities for the optimization. In simulations, our results closely match the results from (Aref and Chagnon, 2022) for the additive white Gaussian noise channel and a simplified model of the intensity-modulation direct-detection channel.","PeriodicalId":13065,"journal":{"name":"IEEE Photonics Technology Letters","volume":"37 18","pages":"1077-1080"},"PeriodicalIF":2.3,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11039765","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural Architecture Search Generated Phase Retrieval Net for Real-Time Off-Axis Quantitative Phase Imaging 神经结构搜索生成的实时离轴定量相位成像相位检索网络

IF 2.3 3区工程技术

IEEE Photonics Technology Letters Pub Date : 2025-06-18 DOI: 10.1109/LPT.2025.3581063

Xin Shu;Mengxuan Niu;Yi Zhang;Wei Luo;Renjie Zhou

{"title":"Neural Architecture Search Generated Phase Retrieval Net for Real-Time Off-Axis Quantitative Phase Imaging","authors":"Xin Shu;Mengxuan Niu;Yi Zhang;Wei Luo;Renjie Zhou","doi":"10.1109/LPT.2025.3581063","DOIUrl":"https://doi.org/10.1109/LPT.2025.3581063","url":null,"abstract":"In off-axis Quantitative Phase Imaging (QPI), artificial neural networks have been recently applied for phase retrieval with aberration compensation and phase unwrapping. However, the involved neural network architectures are largely unoptimized and inefficient with low inference speed, which hinders the realization of real-time imaging. Here, we propose a Neural Architecture Search (NAS) generated Phase Retrieval Net (NAS-PRNet) for accurate and fast phase retrieval. NAS-PRNet is an encoder-decoder style neural network, automatically found from a large neural network architecture search space through NAS. By modifying the differentiable NAS scheme from SparseMask, we learn the optimized skip connections through gradient descent. Specifically, we implement MobileNet-v2 as the encoder and define a synthesized loss that incorporates phase reconstruction loss and network sparsity loss. NAS-PRNet has achieved high-fidelity phase retrieval by achieving a peak Signal-to-Noise Ratio (PSNR) of 36.7 dB and a Structural SIMilarity (SSIM) of 86.6% as tested on interferograms of biological cells. Notably, NAS-PRNet achieves phase retrieval in only 31 ms, representing <inline-formula> <tex-math>$15times $ </tex-math></inline-formula> speedup over the most recent Mamba-UNet with only a slightly lower phase retrieval accuracy.","PeriodicalId":13065,"journal":{"name":"IEEE Photonics Technology Letters","volume":"37 18","pages":"1069-1072"},"PeriodicalIF":2.3,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11039840","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Symbol-Block Ciphering With CBC Mode for Secure Digital Coherent Optical Communication 安全数字相干光通信的CBC模式符号块加密

IF 2.3 3区工程技术

IEEE Photonics Technology Letters Pub Date : 2025-06-17 DOI: 10.1109/LPT.2025.3580417

Reika Suketomo;Keiji Shimada;Hodaka Amano;Takahiro Kodama

引用次数: 0

Machine Learning Enhanced Single Crystal Fiber Fabrication via Laser Heated Pedestal Growth 机器学习增强单晶光纤在激光加热基座生长中的制备

IF 2.3 3区工程技术

IEEE Photonics Technology Letters Pub Date : 2025-06-17 DOI: 10.1109/LPT.2025.3580586

Xibao Gao;Sichao Wang;Bo Liu;Xiao Liu;Shuai Qu;Chen Guan;Qinglan Wang

{"title":"Machine Learning Enhanced Single Crystal Fiber Fabrication via Laser Heated Pedestal Growth","authors":"Xibao Gao;Sichao Wang;Bo Liu;Xiao Liu;Shuai Qu;Chen Guan;Qinglan Wang","doi":"10.1109/LPT.2025.3580586","DOIUrl":"https://doi.org/10.1109/LPT.2025.3580586","url":null,"abstract":"This study introduces a machine learning (ML)-assisted framework for optimizing Proportional-Integral-Derivative (PID) coefficients, enabling stable, long-length single crystal fiber (SCF) fabrication via the Laser Heated Pedestal Growth (LHPG) technique. Compared with traditional curve-fitting methods, the proposed ML approach significantly enhances computational efficiency and achieves up to 20dB improvement in prediction accuracy, leading to notable improvements in SCF uniformity and achievable fiber length. The fabricated sapphire SCF demonstrates a length exceeding 3 m and an average diameter of <inline-formula> <tex-math>$150~mu $ </tex-math></inline-formula>m with fluctuations below <inline-formula> <tex-math>$pm 3~mu $ </tex-math></inline-formula>m, validating the effectiveness of the ML model. Additionally, fundamental guidelines for optimizing PID coefficients in LHPG systems are provided. These results offer valuable insights for high-quality SCF fabrication and are expected to facilitate the production of improved fibers suitable for harsh environment sensing applications.","PeriodicalId":13065,"journal":{"name":"IEEE Photonics Technology Letters","volume":"37 18","pages":"1017-1020"},"PeriodicalIF":2.3,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0