Photonics Research最新文献_第6页

Ultrafast wide-field 3D topography with extended depth of field 具有扩展景深的超快速宽视场三维形貌

IF 7.6 1区物理与天体物理

Photonics Research Pub Date : 2026-09-18 DOI: 10.1364/prj.601894

Qianyi Wei,Jielei Ni,Yuquan Zhang,Zhangyu Zhou,Shuoshuo Zhang,Zhiyong Tan,Jiahui Pan,Xiaocong Yuan,Changjun Min

引用次数: 0

Flexible parallel random bit generation based on chaos-driven electro-optic comb and spectral slicing 基于混沌驱动电光梳和频谱切片的柔性并行随机比特生成

IF 7.6 1区物理与天体物理

Photonics Research Pub Date : 2026-09-18 DOI: 10.1364/prj.605478

Shiyu Shi,Yiqun Zhang,Mengjie Zhou,Mingfeng Xu,Jiahao Qian,Qiang Chen,Xianglei Yan,Yinghui Guo,Mingbo Pu,Xiangang Luo

{"title":"Flexible parallel random bit generation based on chaos-driven electro-optic comb and spectral slicing","authors":"Shiyu Shi,Yiqun Zhang,Mengjie Zhou,Mingfeng Xu,Jiahao Qian,Qiang Chen,Xianglei Yan,Yinghui Guo,Mingbo Pu,Xiangang Luo","doi":"10.1364/prj.605478","DOIUrl":"https://doi.org/10.1364/prj.605478","url":null,"abstract":"High-speed random bit generation (RBG) is a cornerstone of modern cryptographic systems and advanced computing applications. Existing chaos-based random bit generators are typically constrained by the bandwidth of a single entropy source, whereas parallel architectures often suffer from high system complexity and limited reconfigurability. Here, we propose and experimentally demonstrate a flexible parallel RBG scheme based on a novel chaotic architecture combining a chaos-driven electro-optic comb with spectral slicing. The system produces an ultra-broadband, spectrally flat continuum with a 3 dB bandwidth of 678.75 GHz. Exploiting this broadband entropy source, up to 54 parallel chaotic channels are flexibly extracted via spectral slicing. Experimental results show a single-channel random bit rate of 160 Gbps and an aggregate throughput of up to 8.64 Tbps, with all generated bit streams successfully passing the NIST SP 800-22 statistical tests. The proposed scheme not only overcomes the bandwidth bottleneck imposed by the relaxation oscillation limit of single-channel lasers but also enables reconfigurable output settings to accommodate dynamically evolving application requirements. This work opens a scalable route toward high-speed parallel RBG and holds strong promise for next-generation applications, including secure optical communications and stochastic computing.","PeriodicalId":20048,"journal":{"name":"Photonics Research","volume":"19 1","pages":"4359"},"PeriodicalIF":7.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149020144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optical diffractive layers 3D-integrated on a silicon photonic chip for high-density optical neural networks 用于高密度光学神经网络的光学衍射层三维集成在硅光子芯片上

IF 7.6 1区物理与天体物理

Photonics Research Pub Date : 2026-09-18 DOI: 10.1364/prj.591330

Weihong Shen,Tingting Ni,Chao Meng,Haoyi Yu,Ruojing Ren,Min Gu,Qiming Zhang

{"title":"Optical diffractive layers 3D-integrated on a silicon photonic chip for high-density optical neural networks","authors":"Weihong Shen,Tingting Ni,Chao Meng,Haoyi Yu,Ruojing Ren,Min Gu,Qiming Zhang","doi":"10.1364/prj.591330","DOIUrl":"https://doi.org/10.1364/prj.591330","url":null,"abstract":"Optical neural networks (ONNs) have garnered significant interest for their potential to deliver ultra-high computational bandwidth and energy efficiency. Current ONN implementations mainly fall into two categories: integrated photonic neural networks (IPNNs) and free-space diffractive optical neural networks (DONNs). However, IPNNs face challenges in network scalability due to their physical footprints and accumulated losses. DONNs offer high neuron density and spatial parallelism, but possess poor reconfigurability after fabrication. In this work, we propose, to our knowledge, a novel “2D + 3D” hybrid integrated optical neural network (HIONN) architecture that monolithically integrates a 3D optical diffractive layer onto 2D photonic chips via two-photon nanolithography. An array of vertical grating couplers facilitates the optical interconnection between the planar waveguides and 3D free space. This architecture combines the potential programmability and high-speed operation of PICs with the massive parallelism and density of 3D diffractive networks, thereby overcoming the intrinsic limitations of each implementation. As a proof of concept, we experimentally demonstrate the HIONN with a neuron density of 2.5×10 5 neurons/ mm 2 through a pattern recognition task and numerically evaluate its image edge-extraction capability. The proposed HIONN provides a proof-of-concept route toward high-density hybrid integrated optical neural networks and motivates future work on complex and high-throughput optical computing tasks.","PeriodicalId":20048,"journal":{"name":"Photonics Research","volume":"47 1","pages":"4317"},"PeriodicalIF":7.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149020123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Model-free autoencoder for adaptive optimization in turbulent underwater optical wireless communication systems 湍流水下无线光通信系统自适应优化的无模型自编码器

IF 7.6 1区物理与天体物理

Photonics Research Pub Date : 2026-09-18 DOI: 10.1364/prj.592449

Qiarong Xiao,Geyang Wang,Chen Ding,Li Fan,Chao Zhang,Cong Liu,Anzi Xu,Lian-Kuan Chen,Chester Shu,Chaoran Huang

{"title":"Model-free autoencoder for adaptive optimization in turbulent underwater optical wireless communication systems","authors":"Qiarong Xiao,Geyang Wang,Chen Ding,Li Fan,Chao Zhang,Cong Liu,Anzi Xu,Lian-Kuan Chen,Chester Shu,Chaoran Huang","doi":"10.1364/prj.592449","DOIUrl":"https://doi.org/10.1364/prj.592449","url":null,"abstract":"Underwater optical wireless communication (UOWC) is a promising candidate for extending future 6G networks toward underwater connectivity, enabling high-rate links in ocean environments. However, its performance can be constrained by dynamic channel impairments such as turbulence and link misalignment, which make reliable and adaptive transmission particularly challenging for next-generation wireless systems. In response, we propose a model-free autoencoder (AE) framework that enables adaptive, robust, and high-capacity UOWC without relying on explicit channel modeling. Based on deep learning, the framework embeds the physical UOWC channel directly in the forward pass while using a highly simplified backward pass for gradient propagation, allowing end-to-end system optimization under diverse and time-varying conditions. We apply the approach to multi-carrier geometric constellation shaping (GCS). Experiments in a bubble-induced turbulent channel demonstrate rapid adaptation to turbulence variations and clear generalized mutual information (GMI) improvements over model-based AE. Furthermore, extending the framework to a 2×2 MIMO link, we jointly train a CNN-based combiner with the GCS modules. Simulation results show that our method achieves up to 0.57 bits/IQ symbol GMI gain over conventional combining schemes and up to 3.8 dB transmit-power reduction at a target information rate. Experiments in a bubble-induced turbulent MIMO setup further validate its effectiveness and scalability. Our framework offers strong potential for future intelligent and self-adapting UOWC systems operating in complex underwater environments.","PeriodicalId":20048,"journal":{"name":"Photonics Research","volume":"21 1","pages":"4383"},"PeriodicalIF":7.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149020136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Synthesizing high-quality beams via principal modes in a multimode fiber 在多模光纤中通过主模合成高质量光束

IF 7.6 1区物理与天体物理

Photonics Research Pub Date : 2026-09-18 DOI: 10.1364/prj.598956

Jianzhi Zeng,Han Gao,Qiwei Xu,Qiwen Zhan,Haifeng Hu

{"title":"Synthesizing high-quality beams via principal modes in a multimode fiber","authors":"Jianzhi Zeng,Han Gao,Qiwei Xu,Qiwen Zhan,Haifeng Hu","doi":"10.1364/prj.598956","DOIUrl":"https://doi.org/10.1364/prj.598956","url":null,"abstract":"Multimode fibers offer exceptional potential for photonic applications, yet their output is typically scrambled into speckle patterns due to modal interference. While transmission-matrix-based wavefront shaping can recover desired fields at the fiber facet, its sensitivity to wavelength variations and the rapid diffraction of output beams in free space remain key limitations. To overcome these challenges, we extend the concept of principal modes of multimode fiber to tailor not only the field at the output plane but also its subsequent evolution in free space. By engineering the input wavefront to excite dispersion-robust modes with specific propagation characteristics, we experimentally demonstrate output beams that retain a well-confined spatial profile over an extended axial range. These modes exhibit significantly improved directional stability compared to conventional principal modes, effectively bridging the gap between complex multimode waveguides and the need for stable, high-quality free-space beams. This work establishes a framework for using multimode fibers as controllable sources of stable, well-confined free-space beams, with direct implications for beam delivery, free-space optical links, and far-field imaging, while also providing a foundation for multidimensional wavefront control in complex photonic systems.","PeriodicalId":20048,"journal":{"name":"Photonics Research","volume":"191 1","pages":"4338"},"PeriodicalIF":7.6,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149020139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Breaking the Rayleigh scattering limit for deep sub-wavelength wafer defect inspection with circularly polarized interferometry 圆偏振干涉法检测深亚波长晶圆缺陷时突破瑞利散射极限

IF 7.6 1区物理与天体物理

Photonics Research Pub Date : 2026-09-17 DOI: 10.1364/prj.606852

guofeng zhang,Boyu Zhan,Chuanxiang Li,Jingzong Zhang,Peirui Ji,Shuming Yang

引用次数: 0

Dimension-Decoupled and Parameter-Sweep-Free Analytical Inversion for Integrated Vectorial Metasurfaces 集成向量元曲面的尺寸解耦和无参数扫描解析反演

IF 7.6 1区物理与天体物理

Photonics Research Pub Date : 2026-09-17 DOI: 10.1364/prj.600382

Shaodong Zhou,kelei xi,Sheng Xiaohang,Haozong Zhong,Jingxiang Gao,Zhiqiang Wu,Zhenyu Jiang,zijian yao,Lin Li,Yuanjin Zheng,Songlin Zhuang,Yong Liu,Qing Cheng

引用次数: 0

Compact hyperspectral-3D imaging system via lightweight spatial-spectral collaborative reconstruction 基于轻量空间-光谱协同重建的紧凑高光谱-三维成像系统

IF 7.6 1区物理与天体物理

Photonics Research Pub Date : 2026-09-17 DOI: 10.1364/prj.607958

Tongshuo Zhang,Yu Zhenming,Wei Zhang,Liming Cheng,Jingyue Ma,jiayu di,Ning Zhan,Liang Lin,yu zhang,Wenbo Ding,Zaiwei Cao,Kun Xu

引用次数: 0

Mid-Infrared InAsSb pBn Detector Monolithically Integrated on Silicon 硅单片集成中红外InAsSb pBn探测器

IF 7.6 1区物理与天体物理

Photonics Research Pub Date : 2026-09-16 DOI: 10.1364/prj.607478

Le Qin,Dong Han,Fanlong Meng,JINYU ZHANG,JIAXIN YUE,RENJIE WEN,Yutong Jiang,Leran Zhao,CAIXIA SONG,Chunhua Du,Yang Jiang,Hong Chen,Zihao Wang,Ting Wang,Zhang Jianjun,Zhen Deng

引用次数: 0

Impact of Pixel Expressivity on Coarsely Sampled Multi-Plane Light Converters 像素表现力对粗采样多平面光转换器的影响

IF 7.6 1区物理与天体物理

Photonics Research Pub Date : 2026-09-16 DOI: 10.1364/prj.605533

John Aziz,Seth Smith-Dryden,Guifang Li

引用次数: 0