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Asia communications and Photonics Conference and Exhibition (ACP)

作者： Yuansheng Tao Zihan Tao Haowen Shu Ming Jin Xingjun Wang State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing China Frontier Science Center for Nano-optoelectronics Peking University Beijing China Peking University Yangtze Delta Institute of Optoelectronics Nantong China Peng Cheng Laboratory Shenzhen China

We demonstrate the first photonic-based fully integrated microwave instantaneous frequency measurement system, showing a wideband measurement range of 2–34 GHz and an ultralow estimation error of 10.85 MHz.

ISBN: (纸本)9781957171005

关键词： Microwave measurement Estimation error Electronic warfare Measurement uncertainty Asia Microwave communication Frequency estimation

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Multi-scale Sparse Representation-Based Shadow Inpainting for Retinal OCT Images

arXiv

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arXiv 2022年

作者： Tang, Yaoqi Li, Yufan Liu, Hongshan Li, Jiaxuan Jin, Peiyao Gan, Yu Ling, Yuye Su, Yikai John Hopcroft Center for Computer Science Shanghai Jiao Tong University Shanghai200240 China Department of Electrical and Computer Engineering The University of Alabama AL35487 United States Department of Ophthalmology Shanghai General Hospital Shanghai Jiao Tong University Shanghai200080 China State Key Lab of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China

Inpainting shadowed regions cast by superficial blood vessels in retinal optical coherence tomography (OCT) images is critical for accurate and robust machine analysis and clinical diagnosis. Traditional sequence-based approaches such as propagating neighboring information to gradually fill in the missing regions are cost-effective. But they generate less satisfactory outcomes when dealing with larger missing regions and texture-rich structures. Emerging deep learning-based methods such as encoder-decoder networks have shown promising results in natural image inpainting tasks. However, they typically need a long computational time for network training in addition to the high demand on the size of datasets, which makes it difficult to be applied on often small medical datasets. To address these challenges, we propose a novel multi-scale shadow inpainting framework for OCT images by synergically applying sparse representation and deep learning: sparse representation is used to extract features from a small amount of training images for further inpainting and to regularize the image after the multi-scale image fusion, while convolutional neural network (CNN) is employed to enhance the image quality. During the image inpainting, we divide preprocessed input images into different branches based on the shadow width to harvest complementary information from different scales. Finally, a sparse representation-based regularizing module is designed to refine the generated contents after multi-scale feature aggregation. Experiments are conducted to compare our proposal versus both traditional and deep learning-based techniques on synthetic and real-world shadows. Results demonstrate that our proposed method achieves favorable image inpainting in terms of visual quality and quantitative metrics, especially when wide shadows are presented. © 2022, CC BY.

关键词： Image fusion

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A controllable coupling structure for silicon microring resonators based on adiabatic elimination

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Chinese Optics Letters 2020年第1期18卷 110-114页

作者： Fenghe Yang Pengfei Sun Ruixuan Chen Zhiping Zhou State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China Peking University Shenzhen Research Institute Shenzhen 518057China Nano-optoelectronics Frontier Center of Ministry of Education Peking UniversityBeijing 100871China

optical microring resonators are extensively employed in a wide range of physical studies and applications due to the resonance enhancement *** coupling control of a microring resonator is necessary in many scenarios,but modifications are essentially added to the resonator and impair the capability of optical ***,we propose a flexible coupling structure based on adiabatic elimination that allows low-loss active coupling control without any modifications to the *** self-coupling coefficient can be monotonically or non-monotonically controllable by the proposed coupler,potentially at a high *** characteristic of the coupler when implemented in silicon microring resonators is investigated in detail using substantiated analytical theory and *** work provides a general method in coupling control while ensuring the resonance enhancement property,making active coupling control in a resonator-waveguide system feasible.

关键词： silicon photonics adiabatic elimination resonance system

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Self-Adaptive Over-the-Air RF Self-Interference Cancellation based on Signal-of-Interest Driven Regular Triangle Algorithm

Self-Adaptive Over-the-Air RF Self-Interference Cancellation...

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optical Fiber communication (OFC) Conference

作者： Lizhuo Zheng Zhiyang Liu Shilin Xiao Zhiyi Zhang Qidi Liu Mable P. Fok The State key laboratory of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai China Lightwave and Microwave Photonics Laboratory University of Georgia Athens Georgia USA

A signal-of-interest driven self-adaptive RF self-interference cancellation system has been proposed based on regular-triangle algorithm. A weak 16-QAM OFDM signal-of-interest at 18.35GHz has been successfully retriev... 详细信息

ISBN: (数字)9781943580712

ISBN: (纸本)9781728167626

关键词： Algorithms optical signals Orthogonal frequency division multiplexing Silicon carbide Silicon on insulator Visible light

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A GCN-assisted deep learning method for peripapillary retinal layer segmentation in OCT images 25

A GCN-assisted deep learning method for peripapillary retina...

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optical Coherence Tomography and Coherence Domain optical Methods in Biomedicine XXV 2021

作者： Li, Jiaxuan Ling, Yuye He, Jiangnan Jin, Peiyao Zhu, Jianfeng Zou, Haidong Xu, Xun Shao, Shuo Gan, Yu Su, Yikai John Hopcroft Center for Computer Science Shanghai Jiao Tong University Shanghai200240 China Department of Preventative Ophthalmology Shanghai Eye Disease Prevention and Treatment Center Shanghai Eye Hospital Shanghai200040 China Department of Ophthalmology Shanghai Jiao Tong University Shanghai General Hospital Shanghai200080 China Department of Electrical and Computer Engineering The University of Alabama AL35487 United States Department of Electronic Engineering State Key Lab of Advanced Optical Communication Systems and Networks Shanghai Jiao Tong University Shanghai200240 China

ISBN: (数字)9781510640962

ISBN: (纸本)9781510640955

Accurate retinal layer segmentation, especially the peripapillary retinal nerve fiber layer (RNFL) is critical for the diagnosis of ophthalmic diseases. However, due to the complex morphologies of the peripapillary region, most of the existing methods focus on segmenting the macular region and could not be directly applied to the peripapillary retinal optical coherence tomography (OCT) images. In this paper, we propose a novel graph convolutional network (GCN)-assisted segmentation framework based on a U-shape neural network for peripapillary retinal layer segmentation in OCT images. We argue that the strictly stratified structure of retina layers in addition to the centered optic disc is an ideal objective for GCN. Specifically, a graph reasoning block is inserted between the encoder and decoder of the U-shape neural network to conduct spatial reasoning. In this way, the peripapillary retina in OCT images is segmented into nine layers including RNFL. The proposed method was trained and tested on our collected dataset of peripapillary retinal OCT images. Experimental results showed that our segmentation method outperformed other state-of-the-art methods. In particular, compared with ReLayNet, the average and RNFL Dice coefficients are improved by 1.2% and 2.6%, respectively. © 2021 SPIE.

关键词： optical tomography

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Propagation effects of seeded collective emission by two-photon excited oxygen atoms

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Physical Review Research 2023年第4期5卷 043293-043293页

作者： Xin Wang Yu-Hung Kuan Jun Jie Cui Yu Kun Yang Fan Xing Wen-Te Liao Luqi Yuan Yongjun Cheng Zeyang Liao Zheng Li Song Bin Zhang School of Physics and Information Technology Shaanxi Normal University Xi'an 710119 China School of Physics Sun Yat-Sen University Guangzhou 510275 China Department of Physics National Central University Taoyuan City 32001 Taiwan Republic of China School of Physics Henan Normal University Xinxiang 453007 China Physics Division National Center for Theoretical Sciences Taipei 10617 Taiwan Republic of China Quantum Technology Center National Central University Taoyuan City 32001 Taiwan Republic of China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China State Key Laboratory for Mesoscopic Physics and Collaborative Innovation Center of Quantum Matter School of Physics Peking University Beijing 100871 China Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan Shanxi 030006 China Peking University Yangtze Delta Institute of Optoelectronics Nantong Jiangsu 226010 China

A strong ultraviolet pumping laser propagating through the atmosphere could activate the medium and produce the forward and backward coherent air lasing. In this work, we present the theoretical analyses of forward and backward lasing dynamics in the long gain medium consisting of oxygen atoms. By numerically solving the semiclassical Maxwell-Bloch equations, we demonstrate that the atom density, the gain medium length, and the collisional decoherence rate substantially regulate the forward and backward air laser radiation at 845 nm. Especially, our study points out that lower atom density and moderate collisional decoherence rate are favorable for the backward radiation amplification in a long medium, since such conditions balance the competing processes of forward and backward radiation fields. The simulation shows that long medium backward air lasing becomes challenging in the oxygen atom system via double-photon pump, because the amplification can only occur around z=0, and the amplified backward radiation does not carry the spectral information of atoms throughout the medium. On the other hand, certain mechanisms such as variation of backward-seeding delay could possibly alleviate the suppression of backward amplification.

关键词： Air lasing Collective effects in quantum optics Quantum optics Ultrafast optics

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Fast and accurate optical fiber channel modeling using generative adversarial network

arXiv

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arXiv 2020年

作者： Yang, Hang Niu, Zekun Xiao, Shilin Fang, Jiafei Liu, Zhiyang Fainsin, David Yi, Lilin State Key Laboratory of Advanced Optical Communication System and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China IMT Atlantique 2 rue Alfred Kastler Nantes44307 France

In this work, a new data-driven fiber channel modeling method, generative adversarial network (GAN) is investigated to learn the distribution of fiber channel transfer function. Our investigation focuses on joint channel effects of attenuation, chromic dispersion, self-phase modulation (SPM), and amplified spontaneous emission (ASE) noise. To achieve the success of GAN for channel modeling, we modify the loss function, design the condition vector of input and address the mode collapse for the long-haul transmission. The effective architecture, parameters, and training skills of GAN are also displayed in the paper. The results show that the proposed method can learn the accurate transfer function of the fiber channel. The transmission distance of modeling can be up to 1000 km and can be extended to arbitrary distance theoretically. Moreover, GAN shows robust generalization abilities under different optical launch powers, modulation formats, and input signal distributions. Comparing the complexity of GAN with the split-step Fourier method (SSFM), the total multiplication number is only 2% of SSFM and the running time is less than 0.1 seconds for 1000-km transmission, versus 400 seconds using the SSFM under the same hardware and software conditions, which highlights the remarkable reduction in complexity of the fiber channel modeling. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Effective-medium theory for multilayer metamaterials: Role of near-field corrections

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Physical Review B 2020年第17期102卷 174208-174208页

作者： Tong Liu Shaojie Ma Bowen Yang Shiyi Xiao Lei Zhou State Key Laboratory of Surface Physics Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education) and Physics Department Fudan University Shanghai 200433 China Academy for Engineering and Technology Fudan University Shanghai 200433 China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai 200444 China

Although many effective-medium theories have been proposed for studying metamaterials, most of them do not work well for multilayer metamaterials with small interlayer distances. Based on rigorous mode-expansion analyses on a model system consisting of multiple layers of subwavelength gratings, we identify that the failures of conventional effective-medium theories are caused by neglecting strong near-field couplings in homogenizing such systems. These understandings motive us to propose an alternative homogenization approach for strongly coupled multilayer metamaterials, in which predominant near-field corrections have been considered automatically. Our effective-medium theory can well describe multilayer metamaterials with arbitrary interlayer distances including particularly those systems for which conventional effective-medium theories fail. We finally extend our theory to multilayer metamaterials with complicated microstructures and validate the theory by full-wave simulations as well as microwave experiments. Our theory not only well complements the available effective-medium theory formalisms, but also provides a powerful tool to study the properties of strongly coupled metamaterials, which may find many applications in practice.

关键词： Metamaterials Photonics Classical electromagnetism Effective medium approach

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Controlling Unknown Quantum states via Data-Driven state Representations

arXiv

引用

arXiv 2024年

作者： Zhu, Yan Xiao, Tailong Zeng, Guihua Chiribella, Giulio Wu, Ya-Dong QICI Quantum Information and Computation Initiative Department of Computer Science The University of Hong Kong Pokfulam Road Hong Kong State Key Laboratory of Advanced Optical Communication Systems and Networks Institute for Quantum Sensing and Information Processing Shanghai Jiao Tong University Shanghai200240 China Hefei National Laboratory Hefei230088 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Department of Computer Science Parks Road OxfordOX1 3QD United Kingdom Perimeter Institute for Theoretical Physics WaterlooONN2L 2Y5 Canada John Hopcroft Center for Computer Science Shanghai Jiao Tong University Shanghai200240 China

Accurate control of quantum states is crucial for quantum computing and other quantum technologies. In the basic scenario, the task is to steer a quantum system towards a target state through a sequence of control operations. Determining the appropriate operations, however, generally requires information about the initial state of the system. Gathering this information becomes increasingly challenging when the initial state is not a priori known and the system’s size grows large. To address this problem, we develop a machine-learning algorithm that uses a small amount of measurement data to construct its internal representation of the system’s state. The algorithm compares this data-driven representation with a representation of the target state, and uses reinforcement learning to output the appropriate control operations. We illustrate the effectiveness of the algorithm showing that it achieves accurate control of unknown many-body quantum states and non-Gaussian continuous-variable states using data from a limited set of quantum measurements. © 2024, CC BY-NC-SA.

关键词： Reinforcement learning

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10-Gb/s All-Fiber Beamforming LiFi system via Mode-Coupling Control

10-Gb/s All-Fiber Beamforming LiFi System via Mode-Coupling ...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Yiwen Zhang Chao Li Xuebing Zhang Jian Cui Juhao Li Lei Zhu Zilun Li Zizheng Cao Antonius Marcellus Jozef Koonen Chia Wei Hsu University of Southern California Los Angeles California USA Institute for Photonic Integration Eindhoven University of Technology Eindhoven The Netherlands State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Beijing China Division of Vascular Surgery The First Affiliated Hospital Sun Yat-sen University Guangzhou China

By controlling the mode coupling in a multi-mode fiber, we realize an all-fiber and low-cost beamforming transmitter and experimentally demonstrate its application for a 10-Gb/s LiFi system at 1550 nm.

ISBN: (纸本)9781943580910

关键词： Couplings Array signal processing Transmitters Lasers and electrooptics Light fidelity Control systems Laser beams

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