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Optics Continuum 2025年第4期4卷 915-923页

作者： Kong, Zhiwei Cheng, Tianxiang Zhao, Zhigang Liu, Zhaojun School of Information Science and Engineering Shandong University Qingdao266237 China Key Laboratory of Laser and Infrared System Ministry of Education Shandong University Qingdao266237 China Shandong Provincial Key Laboratory of Laser Technology and Application Shandong University Qingdao266237 China

A compact single-frequency nanosecond fiber & solid-state hybrid laser system at 1030 nm is presented. The seed source, a continuous wave distributed feedback (DFB) laser diode, was first externally modulated with a repetition rate of 1.5 MHz and a pulse duration of 10 ns, whose repetition rate was further lowered to 1 kHz by a pulse picker. Afterwards, three-stage end-pumped Yb:YAG crystal amplifiers were employed for energy scaling. Finally, an average power of 12 W was obtained with a repetition rate of 1 kHz and a linewidth of ∼180 MHz, corresponding to approximately four times the Fourier transform limit (FTL). The beam quality factor (M2) was measured to be 1.18 and 1.20 for the horizontal and vertical directions, respectively. In the future, this high-beam quality front-end laser will be used as the seed source for nanosecond disk laser amplifiers. © 2025 Optica Publishing Group.

关键词： Pulse repetition rate

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Optical neural networks:progress and challenges

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Light(science & Applications) 2024年第11期13卷 2511-2535页

作者： Tingzhao Fu Jianfa Zhang Run Sun Yuyao Huang Wei Xu Sigang Yang Zhihong Zhu Hongwei Chen College of Advanced Interdisciplinary Studies National University of Defense TechnologyChangshaChina Hunan Provincial Key Laboratory of Novel Nano-Optoelectronic Information Materials and Devices National University of Defense TechnologyChangshaChina Nanhu Laser Laboratory National University of Defense TechnologyChangshaChina Department of Electronic Engineering Tsinghua UniversityBeijingChina Beijing National Research Center for Information Science and Technology(BNRist) BeijingChina

Artificial intelligence has prevailed in all trades and professions due to the assistance of big data resources,advanced algorithms,and high-performance electronic ***,conventional computing hardware is inefficient at implementing complex tasks,in large part because the memory and processor in its computing architecture are separated,performing insufficiently in computing speed and energy *** recent years,optical neural networks(ONNs)have made a range of research progress in optical computing due to advantages such as subnanosecond latency,low heat dissipation,and high *** are in prospect to provide support regarding computing speed and energy consumption for the further development of artificial intelligence with a novel computing ***,we first introduce the design method and principle of ONNs based on various optical ***,we successively review the non-integrated ONNs consisting of volume optical components and the integrated ONNs composed of on-chip ***,we summarize and discuss the computational density,nonlinearity,scalability,and practical applications of ONNs,and comment on the challenges and perspectives of the ONNs in the future development trends.

关键词： networks neural hardware

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Few-shot object detection via class encoding and multi-target decoding

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IET Cyber-systems and Robotics 2023年第2期5卷 1-14页

作者： Xueqiang Guo Hanqing Yang Mohan Wei Xiaotong Ye Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhouChina Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province HangzhouChina

The task of few‐shot object detection is to classify and locate objects through a few annotated *** many studies have tried to solve this problem,the results are still not *** studies have found that the class margin significantly impacts the classification and representation of the targets to be *** methods use the loss function to balance the class margin,but the results show that the loss‐based methods only have a tiny improvement on the few‐shot object detection *** this study,the authors propose a class encoding method based on the transformer to balance the class margin,which can make the model pay more attention to the essential information of the features,thus increasing the recognition ability of the ***,the authors propose a multi‐target decoding method to aggregate RoI vectors generated from multi‐target images with multiple support vectors,which can significantly improve the detection ability of the detector for multi‐target *** on Pascal visual object classes(VOC)and Microsoft Common Objects in Context datasets show that our proposed Few‐Shot Object Detection via Class Encoding and Multi‐Target Decoding significantly improves upon baseline detectors(average accuracy improvement is up to 10.8%on VOC and 2.1%on COCO),achieving competitive *** general,we propose a new way to regulate the class margin between support set vectors and a way of feature aggregation for images containing multiple objects and achieve remarkable *** method is implemented on mmfewshot,and the code will be available later.

关键词： Class Margin Few-Shot Object Detection Multi-Target Transformer

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MULTI-ROBOT PATH PLANNING AND COOPERATIVE OBSTACLE AVOIDANCE BASED ON MONTE-CARLO TREE SEARCH 10

MULTI-ROBOT PATH PLANNING AND COOPERATIVE OBSTACLE AVOIDANCE...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Dai, Juan Jing, Yanzhang Su, Zhong Zhu, Cui Beijing Key Laboratory of High Dynamic Navigation Technology Beijing Information Science & Technology University Beijing China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing China School of Automation Beijing Information Science & Technology University Beijing China School of Information and Communication Engineering Beijing Information Science & Technology University Beijing China

ISBN: (纸本)9781837242672

With the rapid development of artificial intelligence technologies, multi-robot cooperative processing tasks are becoming more and more common in various applications. However, traditional single-robot planning algorithms show obvious limitations in dealing with complex social interactions and dynamic environments in the real world. To address this challenge, this paper applies Monte Carlo Tree Search (MCTS) to multi-robot path planning and proposes a collaborative obstacle avoidance motion planning algorithm based on MCTS. Specifically, the algorithm prunes the Monte Carlo tree by excluding cases that do not meet the robot speed constraints and potential collisions, which significantly improves the computational speed and success rate of the algorithm, making it applicable to the multi-robot path conflict problem. In addition, we design a policy space that conforms to the robot's operation and a cost function that meets the requirements of robot path planning to plan an efficient cooperative path for each robot. Through a series of simulation experiments, we demonstrate the algorithm's path planning and obstacle avoidance performance in a variety of conflict scenarios. The results show that the method is highly cooperative and effective in complex environments. © The Institution of engineering & technology 2024.

关键词： Cost functions

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A reposition algorithm for e-hailing based on quantum annealing and intuitive reasoning

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Intelligent and Converged Networks 2024年第4期5卷 317-335页

作者： Chao Wang Yiyun Shi Sumin Wang Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai UniversityShanghai 200444China School of Information Engineering Ganzhou Key Laboratory of Cloud Computing and Big Data ResearchGannan University of Science and TechnologyGanzhou 341000China

Currently,the challenge lies in the traditional intelligent algorithm’s ability to effectively address the e-hailing repositioning *** identifying the underlying characteristics in extensive traffic data within a limited timeframe is difficult,ultimately preventing the achievement of the most optimal *** paper suggests a hybrid computing architecture involving reinforcement learning and quantum annealing based on intuitive *** reasoning aims to enhance performance in scenarios with poor system robustness,complex tasks,and diverse goals.A deep learning model is constructed,trained to extract scene features,and combined with expert knowledge,then transformed into a quantum annealable *** final strategy is obtained using a D-wave quantum computer with quantum tunneling effect,which helps in finding optimal solutions by jumping out of local suboptimal *** on 400000 real data,four algorithms are compared:minimum-cost flow,sequential markov decision process,hot-dot strategy,and driver-prefer *** average total revenue increases by about 10%and vehicle utilization by about 15%in various *** summary,the proposed architecture effectively solves the e-hailing reposition problem,offering new directions for robust artificial intelligence in big data decision problems.

关键词： intuitive reasoning reinforcement learning quantum annealing

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Robust twin-field quantum key distribution through sending or not sending

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National science Review 2023年第4期10卷 76-85页

作者： Cong Jiang Zong-Wen Yu Xiao-Long Hu Xiang-Bin Wang Jinan Institute of Quantum Technology State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Data Communication Science and Technology Research Institute School of Physics State Key Laboratory of Optoelectronic Materials and Technologies Sun Yat-sen University Shanghai Branch CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Shenzhen Institute for Quantum Science and Engineering and Physics Department Southern University of Science and Technology Frontier Science Center for Quantum Information

The sending-or-not-sending(SNS) protocol is one of the most major variants of the twin-field(TF)quantum key distribution(QKD) protocol and has been realized in a 511-km field fiber, the farthest field experiment to date. In practice, however, all decoy-state methods have unavoidable source errors, and the source errors may be non-random, which compromises the security condition of the existing TF-QKD protocols. In this study, we present a general approach for efficiently calculating the SNS protocol's secure key rate with source errors, by establishing the equivalent protocols through virtual atenuation and the tagged model. This makes the first result for TF QKD in practice where source intensity cannot be controlled exactly. Our method can be combined with the two-way classical communication method such as active odd-parity pairing to further improve the key rate. The numerical results show that if the intensity error is within a few percent, the key rate and secure distance only decrease marginally. The key rate of the recent SNS experiment in the 511-km field fiber is still positive using our method presented here, even if there is a ±9.5% intensity fluctuation. This shows that the SNS protocol is robust against source errors.

关键词： quantum information quantum key distribution sending or not sending twin field source error

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An embedded vertical‐federated feature selection algorithm based on particle swarm optimisation

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CAAI Transactions on Intelligence technology 2023年第3期8卷 734-754页

作者： Yong Zhang Ying Hu Xiaozhi Gao Dunwei Gong Yinan Guo Kaizhou Gao Wanqiu Zhang School of Information and Control Engineering China University of Mining and TechnologyXuzhouChina The Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchunChina School of Computing University of Eastern FinlandKuopioFinland The Macao Institute of Systems Engineering Macao University of Science and TechnologyTaipaChina

In real life,a large amount of data describing the same learning task may be stored in different institutions(called participants),and these data cannot be shared among par-ticipants due to privacy *** case that different attributes/features of the same instance are stored in different institutions is called vertically distributed *** pur-pose of vertical‐federated feature selection(FS)is to reduce the feature dimension of vertical distributed data jointly without sharing local original data so that the feature subset obtained has the same or better performance as the original feature *** solve this problem,in the paper,an embedded vertical‐federated FS algorithm based on particle swarm optimisation(PSO‐EVFFS)is proposed by incorporating evolutionary FS into the SecureBoost framework for the first *** optimising both hyper‐parameters of the XGBoost model and feature subsets,PSO‐EVFFS can obtain a feature subset,which makes the XGBoost model more *** the same time,since different participants only share insensitive parameters such as model loss function,PSO‐EVFFS can effec-tively ensure the privacy of participants'***,an ensemble ranking strategy of feature importance based on the XGBoost tree model is developed to effectively remove irrelevant features on each ***,the proposed algorithm is applied to 10 test datasets and compared with three typical vertical‐federated learning frameworks and two variants of the proposed algorithm with different initialisation ***-mental results show that the proposed algorithm can significantly improve the classifi-cation performance of selected feature subsets while fully protecting the data privacy of all participants.

关键词： Evolutionary optimization feature selection privacy protection vertical‐federated learning

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Recent advances on monolithic perovskite-organic tandem solar cells

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Interdisciplinary Materials 2024年第1期3卷 113-132页

作者： Guanshui Xie Huan Li Longbin Qiu Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Department of Mechanical and Energy EngineeringSUSTech Energy Institute for Carbon NeutralitySouthern University of Science and TechnologyShenzhenChina

Perovskite-organic tandem solar cells(TSCs)have emerged as a groundbreaking technology in the realm of photovoltaics,showcasing remarkable enhancements in efficiency and significant potential for practical ***-organic TSCs also exhibit facile fabrication surpassing that of all-perovskite or all-organic TSCs,attributing to the advantageous utilization of orthogonal solvents enabling sequential solution process for each *** perovskite-organic TSCs capitalize on the complementary light absorption characteristics of perovskite and organic *** is a promising prospect of achieving further enhanced power conversion efficiencies by covering a broad range of the solar spectrum with optimized perovskite absorber,organic semiconductors as well as the interconnecting layer's optical and electrical *** review comprehensively analyzes the recent advancements in perovskite-organic TSCs,highlighting the synergistic effects of combining perovskite with a low open-circuit voltage deficit,organic materials with broader light absorption,and interconnecting layers with reduced optical and electrical ***,the underlying device architecture design,regulation strategies,and key challenges facing the high performance of the perovskite-organic TSCs are also discussed.

关键词： interconnecting layer narrow‐bandgap organic solar cells recombination layer tandem solar cells wide‐bandgap perovskite solar cells

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UKF‐MOT:An unscented Kalman filter‐based 3D multi‐object tracker

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CAAI Transactions on Intelligence technology 2024年第4期9卷 1031-1041页

作者： Meng Liu Jianwei Niu Yu Liu Collective Intelligence&Collaboration Laboratory China North Artificial Intelligence and Innovation Research InstituteBeijingChina China North Vehicle Research Institute BeijingChina State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijingChina State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina School of Computer Science and Engineering Beihang UniversityBeijingChina

Multi‐object tracking in autonomous driving is a non‐linear *** better address the tracking problem,this paper leveraged an unscented Kalman filter to predict the object's *** the association stage,the Mahalanobis distance was employed as an affinity metric,and a Non‐minimum Suppression method was designed for *** the detections fed into the tracker and continuous‘predicting‐matching’steps,the states of each object at different time steps were described as their own continuous *** conducted extensive experiments to evaluate tracking accuracy on three challenging datasets(KITTI,nuScenes and Waymo).The experimental results demon-strated that our method effectively achieved multi‐object tracking with satisfactory ac-curacy and real‐time efficiency.

关键词： autonomous vehicle transportation

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Global output feedback adaptive stabilization for systems with long uncertain input delay

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science China(information sciences) 2023年第1期66卷 326-327页

作者： Zhuping WANG Jingcheng LIU Chao HUANG Hao ZHANG Huaicheng YAN School of Electronics and Information Engineering Tongji University Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education East China University of Science and Technology

Dear editor,The uncertain input delay is frequently encountered in engineering control systems. Adaptation is indispensable when the uncertain input delay is significant. In existing delayadaptive controllers [1–6], the actuator state must be measured to achieve global stability. Recently, a logic-based switching delay-adaptive state-feedback controller [7] was proposed to realize global stability without measuring the actuator state.

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