Author Affiliations
1 Shanghai Jiao Tong University, Department of Electronic Engineering, State Key Laboratory of Advanced Optical Communication Systems and Networks, Shanghai, China
2 Nokia Bell Labs, Murray Hill, New Jersey, United States
3 Shanghai University, Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai, China
4 Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, John Hopcroft Center for Computer Science, Shanghai, China
Mode-division multiplexing (MDM) technology enables high-bandwidth data transmission using orthogonal waveguide modes to construct parallel data streams. However, few demonstrations have been realized for generating and supporting high-order modes, mainly due to the intrinsic large material group-velocity dispersion (GVD), which make it challenging to selectively couple different-order spatial modes. We show the feasibility of on-chip GVD engineering by introducing a gradient-index metamaterial structure, which enables a robust and fully scalable MDM process. We demonstrate a record-high-order MDM device that supports TE0–TE15 modes simultaneously. 40-GBaud 16-ary quadrature amplitude modulation signals encoded on 16 mode channels contribute to a 2.162 Tbit / s net data rate, which is the highest data rate ever reported for an on-chip single-wavelength transmission. Our method can effectively expand the number of channels provided by MDM technology and promote the emerging research fields with great demand for parallelism, such as high-capacity optical interconnects, high-dimensional quantum communications, and large-scale neural networks.
integrated photonics metamaterial mode-division multiplexing subwavelength grating 
Advanced Photonics
2023, 5(5): 056008
王化宾 1,2何渝 1,2赵立新 1,2,*
1 中国科学院光电技术研究所微细加工光学技术国家重点实验室,四川 成都 610209
2 中国科学院大学,北京 100049
针对目前双面微器件加工方法步骤繁琐、效率低的问题,提出基于改进Gerchberg-Saxton(GS)算法的全息双面光刻方法,使用单个光源在玻璃基底的上下表面同时曝光,进行双面图形的制作。该方法通过计算不同轴向位置图案对应的组合全息图,并将其加载到空间光调制器(LCOS-SLM)上,对入射光场进行调制,从而在目标空间内实现双面图形重现。采用改进GS算法对距离焦面2 mm处的图案A与距离焦面4.06 mm处的图案B进行全息图计算与仿真重建。搭建实验装置,对3 mm厚透明石英玻璃基底的上下表面同时曝光,且对光场生成过程中的散斑、杂散光及串扰问题做出分析并提出解决方案,最终实现60 μm线宽双层图案曝光,验证了所提方法进行双面光刻的可行性。所提方法使用单张全息图和单个光源,通过单次曝光即可在目标体积内生成多层任意图形,极大地简化了双面图形制作的步骤。
计算全息 微纳制造 双面光刻 光场调控 全息算法 computer-generated holography micro and nano manufacturing double-sided photolithography light field modulation holographic algorithm 
2023, 60(16): 1609001
Yu He 1†Yunhua Yao 1Yilin He 1Zhengqi Huang 1[ ... ]Shian Zhang 1,5,6,*
Author Affiliations
1 East China Normal University, School of Physics and Electronic Science, State Key Laboratory of Precision Spectroscopy, Shanghai, China
2 Shenzhen University, Institute of Microscale Optoelectronics, Nanophotonics Research Center, Shenzhen Key Laboratory of Micro-Scale Optical Information Technology, Shenzhen, China
3 Peking University, Biomedical Engineering Department, Beijing, China
4 Peking University, School of Physics, State Key Laboratory for Mesoscopic Physics and Frontiers Science Center for Nano-optoelectronics, Beijing, China
5 East China Normal University, Joint Research Center of Light Manipulation Science and Photonic Integrated Chip of East China Normal University and Shandong Normal University, Shanghai, China
6 Shanxi University, Collaborative Innovation Center of Extreme Optics, Taiyuan, China
Structured illumination microscopy (SIM) has been widely applied in the superresolution imaging of subcellular dynamics in live cells. Higher spatial resolution is expected for the observation of finer structures. However, further increasing spatial resolution in SIM under the condition of strong background and noise levels remains challenging. Here, we report a method to achieve deep resolution enhancement of SIM by combining an untrained neural network with an alternating direction method of multipliers (ADMM) framework, i.e., ADMM-DRE-SIM. By exploiting the implicit image priors in the neural network and the Hessian prior in the ADMM framework associated with the optical transfer model of SIM, ADMM-DRE-SIM can further realize the spatial frequency extension without the requirement of training datasets. Moreover, an image degradation model containing the convolution with equivalent point spread function of SIM and additional background map is utilized to suppress the strong background while keeping the structure fidelity. Experimental results by imaging tubulins and actins show that ADMM-DRE-SIM can obtain the resolution enhancement by a factor of ∼1.6 compared to conventional SIM, evidencing the promising applications of ADMM-DRE-SIM in superresolution biomedical imaging.
structured illumination microscopy superresolution imaging resolution enhancement untrained neural network 
Advanced Photonics Nexus
2023, 2(4): 046005
Yilin He 1†Yunhua Yao 1Dalong Qi 1Yu He 1[ ... ]Shian Zhang 1,4,*
Author Affiliations
1 East China Normal University, School of Physics and Electronic Science, State Key Laboratory of Precision Spectroscopy, Shanghai, China
2 Shenzhen University, Institute of Microscale Optoelectronics, Nanophotonics Research Center, Shenzhen Key Laboratory of Micro-Scale Optical Information Technology, Shenzhen, China
3 Peking University, School of Physics, Frontiers Science Center for Nanooptoelectronics, State Key Laboratory for Mesoscopic Physics, Beijing, China
4 Shanxi University, Collaborative Innovation Center of Extreme Optics, Taiyuan, China
Various super-resolution microscopy techniques have been presented to explore fine structures of biological specimens. However, the super-resolution capability is often achieved at the expense of reducing imaging speed by either point scanning or multiframe computation. The contradiction between spatial resolution and imaging speed seriously hampers the observation of high-speed dynamics of fine structures. To overcome this contradiction, here we propose and demonstrate a temporal compressive super-resolution microscopy (TCSRM) technique. This technique is to merge an enhanced temporal compressive microscopy and a deep-learning-based super-resolution image reconstruction, where the enhanced temporal compressive microscopy is utilized to improve the imaging speed, and the deep-learning-based super-resolution image reconstruction is used to realize the resolution enhancement. The high-speed super-resolution imaging ability of TCSRM with a frame rate of 1200 frames per second (fps) and spatial resolution of 100 nm is experimentally demonstrated by capturing the flowing fluorescent beads in microfluidic chip. Given the outstanding imaging performance with high-speed super-resolution, TCSRM provides a desired tool for the studies of high-speed dynamical behaviors in fine structures, especially in the biomedical field.
super-resolution microscopy high-speed imaging compressive sensing deep learning image reconstruction 
Advanced Photonics
2023, 5(2): 026003
王虎 1,2何渝 1,*
1 中国科学院光电技术研究所,四川 成都 610209
2 中国科学院大学, 北京 100049
计算全息 曲面投影 光刻 computer generated holography curved surfaces projection optical lithography 
2022, 51(11): 20220136
Xinyu Chen 1Honghao Cao 1,25 1Yue He 1[ ... ]Chong Hou 1,*
1 School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
2 Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge 02139, USA
3 Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China
4 State Key Laboratory of Materials Processing and Die and Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
5 Research Institute of Huazhong University of Science and Technology in Shenzhen, Shenzhen 518063, China
Functional nanofiber Nanofiber fabrication Nanofiber structure Nanofiber materials Nanofiber assembly 
Frontiers of Optoelectronics
2022, 15(4): s12200
金川 1,2何渝 2唐燕 2刘俊伯 2[ ... ]胡松 2,*
1 中国科学院大学,北京 100049
2 中国科学院光电技术研究所,四川 成都 610209

微离轴数字全息 空间失配标定 粒子群优化算法 slightly off-axis digital holography spatial mismatch calibration particle swarm optimization algorithm 
2022, 49(9): 220047
成科 1,2,*胡晓楠 1,2贺瑜 1,2孟维佳 1,2[ ... ]方心远 1,2
1 上海理工大学光子芯片研究院, 上海 200093
2 上海理工大学光电信息与计算机工程学院人工智能纳米光子学中心, 上海 200093
完美涡旋光束 (POVB) 是径向强度分布和半径均与光束轨道角动量 (OAM) 状态无关的一类涡旋光, 已被应用于光学操控、光通信、激光材料处理等领域。其中, POVB 轨道角动量状态的探测是关键且有挑战的技术。本研究通过并行梯度下降算法, 构建了光学衍射神经网络 (DNN), 实验上实现了轨道角动量阶数在-50~+50 范围内的 POVB 的识别。在此过程中, 衍射转换效率可达 58%。本研究为 POVB 的 OAM 探测提供了新的思路, 在 POVB 的各类应用中均存在潜在应用价值。
傅里叶光学 轨道角动量探测 光学衍射神经网络 完美涡旋光束 Fourier optics orbital angular momentum detection optical diffraction neural network perfect optical vortex beam 
2022, 39(2): 262
中国人民解放军 63618部队, 新疆 库尔勒 841000
红外大气透过率是分析目标红外辐射特性和红外辐射反演计算的重要基础。针对Modtran等大气透过率计算软件难以与红外辐射特性测量系统集成的问题, 在大气透过率经验公式基础上进行推导, 提出一种适用远距离、任意传输路径的红外大气透过率的工程计算方法。方法基于传输路径上的地理位置对大气分层, 使用实测数据提取大气模型参数, 实现中等分辨率远距离中波红外大气透过率的快速工程计算。计算结果表明, 工程计算得到的平均透过率接近Modtran, 且易于与实时系统集成。
大气透过率 大气模型 红外辐射 atmospheric transmittance atmospheric model infrared radiation 
2021, 47(6): 728
兰州大学 核科学与技术学院, 兰州 730000
为了快速定量地分析待测样品中铀元素含量信息, 采用激光诱导击穿光谱技术结合内标法, 通过脉宽为7ns、输出能量为20mJ的纳秒激光脉冲诱导涂有硝酸双氧铀的石墨片产生等离子体光谱, 测量了波长范围为300nm~800nm的光谱数据, 对涂有不同浓度的铀样品进行了定量分析以及理论分析和实验验证, 取得了UⅡ 409.01nm和UⅡ 367.01nm谱线和CⅠ 373.72nm, CⅡ 383.57nm, CⅢ 378.94nm谱线数据。结果表明, 样品浓度低于5.0×10-3mol/m2(本文中研究的是面密度)时, 铀归一化强度与铀浓度存在较好的线性关系, 激光诱导击穿光谱技术与内标法结合可以用于快速定量分析待测样品中铀元素含量信息。该研究为核污染和铀矿中微量铀元素的快速检测分析提供了参考。
激光技术 激光诱导击穿光谱 硝酸双氧铀 定量分析 laser technique laser-induced breakdown spectroscopy uranyl nitrate quantitative analysis 
2021, 45(3): 331

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