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Spatiotemporal mode-locked intelligent fiber laser based on cascaded photonic lanterns

Optics Letters 2025年第2期50卷 463-466页

作者： Liu, Zhuyixiao Zhang, Fengming Qian, Zichen Liu, Jing Dai, Lilong Mou, Chengbo Zhao, Luming Tang, Ming National Engineering Laboratory for Next Generation Internet Access System School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai University Shanghai200444 China

An intelligent controlled spatiotemporal mode-locked (STML) fiber laser based on a photonic lantern (PL) is proposed and experimentally demonstrated. A pair of in-house developed PLs is spliced into the cavity in a back-to-back structure. This PL-based structure functions as a mode multiplexer/demultiplexer to generate higher-order spatial modes. Owing to the strong polarization-dependent loss structural characteristics, the structure also serves as an equivalent saturable absorber based on nonlinear polarization rotation. The STML fiber laser delivers pulsed high-order modes at a center wavelength of 1555.4 nm with a pulse duration of 6.99 ps. With the deployment of a motorized polarization controller and a time-domain signal feedback system, the laser enables intelligent control via a stochastic global polarization search algorithm. Experimental results indicate that the proposed laser can effectively evade disturbances from complex intracavity states and accurately lock onto the fundamental mode-locking state within only 2 min. © 2025 Optica Publishing Group. All rights,including for text and data mining (TDM), Artificial Intelligence (AI)training, and similar technologies, are reserved.

关键词： Time domain analysis

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Time-Varying Formation Tracking Control of Heterogeneous Multi-Agent systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems Control theory Autonomous systems Stability

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Model-Driven Deep Learning-Based Optimization of Downlink Precoding and Fronthaul Compression in Cell-Free MIMO systems

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IEEE Transactions on Network Science and Engineering 2025年第3期12卷 1804-1817页

作者： Chen, Yijie Xia, Wenchao Cai, Shu Zheng, Gan Zhu, Hongbo Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Wireless Communications and Internet of Things Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks Ministry of Education Nanjing210003 China Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Intelligent Information Processing and Communication Technology Nanjing210003 China

Cell-free multiple-input multiple-output (MIMO) system is a promising solution for wireless communications. However, the potential in improving system performance is restricted due to the capacity-limited fronthaul links. To tackle this problem, we utilize the compress-and forward approach, which leverages various compression and encoding techniques to reduce the fronthaul overhead. Thus, jointly optimizing precoding and fronthaul compression presents a significant challenge. However, current optimization algorithms frequently entail high computational complexity because of their iterative processes, rendering impractical for real-time use. To overcome this challenge, we present a model-driven deep learning-based framework to characterize the structure of precoding vectors and the compression matrix via low-dimensional parameters, leveraging the uplink-downlink duality as the expert knowledge. A deep neural network can learn these low-dimensional "key features" from channel state information. Simulation results indicate that our approach achieves performance comparable to the optimal algorithm and substantially reduces complexity. © 2013 IEEE.

关键词： Channel state information

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Understanding the Decoupled Effects of Cations and Anions Doping for High-Performance Perovskite Solar Cells

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Nano-Micro Letters 2025年第6期17卷 411-426页

作者： Tianxiang Hu Yixi Wang Kai Liu Jia Liu Haoyang Zhang Qudrat Ullah Khan Shijie Dai Weifan Qian Ruochen Liu Yanyan Wang Chongyuan Li Zhenru Zhang Mingxiang Luo Xiaofei Yue Chunxiao Cong Yuan Yongbo Anran Yu Jia Zhang Yiqiang Zhan Center of Micro-Nano System School of Information Science and TechnologyFudan UniversityShanghai 200438People’s Republic of China The State Key Laboratory of Photovoltaic Science and Technology Institute of OptoelectronicsFudan UniversityShanghai 200438People’s Republic of China Institute for Electric Light Sources School of Information Science and TechnologyFudan UniversityShanghai 200438People’s Republic of China Hunan Key Laboratory of Nanophotonics and Devices School of PhysicsCentral South UniversityChangsha 410083People’s Republic of China Vanced Materials Technology(Zhongshan)Co. Ltd.Guangdong 528437People’s Republic of China

The past decade has witnessed the rapid increasement in power conversion efficiency of perovskite solar cells(PSCs).However,serious ion migration hampers their operational *** dopants composed of varied cations and anions are introduced into perovskite to suppress ion migration,the impact of cations or anions is not individually explored,which hinders the evaluation of different cations and further application of doping *** we report that a special group of sulfonic anions(like CF_(3)SO_(3)^(-))successfully introduce alkaline earth ions(like Ca^(2+))into perovskite lattice compared to its halide ***,with effective crystallization regulation and defect passivation of sulfonic anions,perovskite with Ca(CF_(3)SO_(3))_(2)shows reduced PbI2 residue and metallic Pb0 defects;thereby,corresponding PSCs show an enhanced PCE of 24.95%.Finally by comparing the properties of perovskite with Ca(CF_(3)SO_(3))_(2)and FACF_(3)SO_(3),we found that doped Ca^(2+)significantly suppressed halide migration with an activation energy of 1.246 eV which accounts for the improved operational stability of Ca(CF_(3)SO_(3))_(2-)doped PSCs,while no obvious impact of Ca^(2+)on trap density is *** the benefits of cations and anions,this study presents an effective method to decouple the effects of cations and anions and fabricate efficient and stable PSCs.

关键词： Perovskite solar cells Interstitial doping Effect decoupling Ion migration

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Chain-of-Specificity: Enhancing Task-Specific Constraint Adherence in Large Language Models 31

Chain-of-Specificity: Enhancing Task-Specific Constraint Adh...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Wei, Kaiwen Zhong, Jiang Zhang, Hongzhi Zhang, Di Jin, Li Yu, Yue Zhang, Jingyuan College of Computer Science Chongqing University China Kuaishou Inc. China Key Laboratory of Network Information System Technology Aerospace Information Research Institute Chinese Academy of Sciences China

ISBN: (纸本)9798891761964

Large Language Models (LLMs) exhibit remarkable generative capabilities, enabling the generation of valuable information. Despite these advancements, previous research found that LLMs sometimes struggle with adhering to specific constraints (e.g., in specific place or at specific time), at times even overlooking them, which leads to responses that are either too generic or not fully satisfactory. Existing approaches attempted to address this issue by decomposing, rewriting input instructions, or reflecting on prior failings, yet they fall short in adequately emphasizing specific constraints and in unlocking the underlying knowledge (e.g., programming within the context of software development). In response, this paper proposes a simple yet effective method Chain-of-Specificity (CoS). Specifically, CoS iteratively emphasizes the specific constraints in the input instructions, unlocks knowledge within LLMs, and refines responses. Experiments conducted on publicly available and self-build complex datasets demonstrate that CoS outperforms existing methods in enhancing generated content especially for the specificity. Besides, as the number of specific constraints increase, other baselines falter, while CoS still performs well. Moreover, we show that distilling responses generated by CoS effectively enhances the ability of smaller models to follow the constrained instructions. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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An Adaptive Thin Cloud Removal Method for Mitigating Bright Surface Interference

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 11487-11501页

作者： Jiang, Tao Shen, Huanfeng Li, Huifang Lin, Dekun Li, Dongyi Wuhan University School of Resource and Environmental Science Wuhan430079 China School of Resource and Environmental Sciences of Wuhan University Key Laboratory of Geographic Information System of Ministry of Education Key Laboratory of Digital Mapping and Land Information Application of the Ministry of Natural Resources Wuhan430079 China Wuhan University School of Resource and Environmental Sciences Collaborative Innovation Center for Geospatial Technology Wuhan430079 China

A thin cloud thickness map (TCTM) is crucial for thin cloud removal tasks, but accurately estimating the TCTM can be a significant challenge. The TCTM is highly susceptible to buildings, which are unavoidable. However, bright surface extraction in existing thin cloud estimation methods is susceptible to thin clouds, affecting the estimation results for the TCTM. In this paper, we propose an adaptive thin cloud removal method for mitigating bright surface interference. Initially, the TCTM is estimated based on the dark pixel search method. The latent low-rank representation (LatentLRR) method is then employed to decompose the TCTM, resulting in a low-rank optimized TCTM. We also propose a new short-wave infrared-based building index (SIBI), which effectively extracts building regions in images that are affected by thin clouds, while remaining largely unaffected by them. Based on this index, an adaptive building suppression weight matrix is constructed to reduce the TCTM for building regions covered by thin clouds. For buildings without cloud cover, the inverse proportional averaging method is used to obtain a fixed weight to suppress the TCTM. Finally, the aerosol thickness in the TCTM is excluded, and the thin cloud reflectivity components for each band are resolved through linear relationships combined with scattering laws, achieving thin cloud removal in single remote sensing images. The experimental results demonstrate that the proposed method can accurately extract the TCTM in various scenarios. The thin cloud removal results exhibit high color and structural consistency with the reference images and achieve optimal spectral fidelity. © 2008-2012 IEEE.

关键词： Inverse problems

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Intensified Tropical Cyclones in Global Climate Simulations Employing a High-Wind Drag Relation over Sea Surface

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Journal of Climate 2025年第10期38卷 2205-2223页

作者： Wei, Wei Lu, Yixiong Yang, Shunan Liu, Yiming Wu, Tongwen Song, Zhenya Qiao, Fangli Li, Yubin Wu, Fanghua Rong, Xinyao Li, Jianglong CMA Earth System Modeling and Prediction Centre China Meteorological Administration Beijing China State Key Laboratory of Severe Weather Meteorological Science and Technology CMA Earth System Modeling and Prediction Centre Beijing China National Meteorological Centre China Meteorological Administration Beijing China First Institute of Oceanography Key Laboratory of Marine Science and Numerical Modeling Ministry of Natural Resources Qingdao China School of Atmospheric Physics Nanjing University of Information Science and Technology Nanjing China

Accurate parameterization of momentum fluxes at high winds across the air–sea interface is crucial for realistically simulating the surface wind fields of tropical cyclones (TCs). Climate models often struggle to reproduce observed TC intensities, particularly surface wind speeds. This study evaluates the performance of a revised surface drag scheme with a capping drag coefficient at high wind speeds in global climate models (GCMs). Our results indicate that the revised surface drag scheme significantly improves the representation of TCs in a statistical sense: (i) Not only the mature intensity but also the maximum 10-m wind speeds throughout the TC life cycle are largely enhanced;(ii) biases in the pressure–wind relationship are notably alleviated, exhibiting reasonable agreement with observations;and (iii) other TC statistical features, such as TC number, central sea level pressure, individual lifetime, and intensification rate, show relatively minor sensitivity to the surface drag schemes. The main reason for the superiority of the revised high-wind drag relation is that the lower drag coefficient in high-wind conditions significantly increases the maximum potential intensity (MPI), indicating a higher theoretical limit for TC intensities. These findings are consistent across different model versions and resolutions, highlighting the robustness of the high-wind surface drag parameterization in controlling the simulated surface wind speeds of TCs in GCMs. © 2025 American Meteorological Society.

关键词： Tropical cyclone

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Brillouin Frequency Shift Extraction for BOTDA Based on Gramian Angular Fields 4

Brillouin Frequency Shift Extraction for BOTDA Based on Gram...

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4th International Computational Imaging Conference, CITA 2024

作者： Zhu, Borong Zhang, Zhihao Qian, Yuhao Ma, Xiaole Wang, Liang Yu, Kuanglu Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China Institute of Information Science School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China National Engineering Laboratory for Next Generation Internet Access System School of Optics and Electronic Information Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781510688834

To accurately extract Brillouin frequency shift of BOTDA with large sweeping step sizes, a novel structure of GAFCNN is proposed, combining time series coding with convolutional neural networks. The experimental data validation results demonstrate that the GAFCNN is capable of obtaining more accurate results under large sweep steps and low signal-to-noise ratios (SNRs) than other current methods. © 2025 SPIE.

关键词： Convolutional neural networks

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Joint Sensing and Computation Incentive Mechanism for Mobile Crowdsensing Networks: A Multiagent Reinforcement Learning Approach

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IEEE Internet of Things Journal 2025年第9期12卷 13033-13046页

作者： Zhao, Nan Sun, Yiling Pei, Yiyang Niyato, Dusit Hubei University of Technology Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Wuhan430061 China Singapore Institute of Technology Information and Communications Technology Cluster Tampines Singapore Nanyang Technological University School of Computer Science and Engineering Jurong West Singapore

Mobile crowdsensing (MCS) is a novel sensing paradigm by utilizing mobile users (MUs) to collect data from environment. Considering the finite sensing and computing resources of MUs, it is crucial to inspire MUs to take part in crowdsensing willingly. In this study, a multiagent-deep-reinforcement-learning (DRL)-based incentive mechanism is investigated to tackle the joint data sensing and computing issues. Specifically, due to the heterogeneity of sensing tasks, multiple MCS platforms (MCPs) motivate MUs to participate in different tasks. The interaction between MCPs and MUs is modeled as a multileader-multifollower Stackelberg game with Stackelberg equilibrium proved by derivation. Moreover, the Stackelberg game is transformed as a Markov decision process (MDP) to deal with a multiagent DRL method without any prior knowledge. Due to the continuous high-dimensional action space of multiple MCPs and MUs, a multiagent double actors deep deterministic policy gradient (MA-DADDPG) algorithm is proposed to obtain the optimal sensing data size, computing resource, and incentive payment policies. Extensive simulation results illustrate the effectiveness of the proposed crowdsensing incentive mechanism. © 2014 IEEE.

关键词： Deep reinforcement learning

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MemoFlow: Modifying Explicit Motion of Inconsistency in Optical Flow 27th

MemoFlow: Modifying Explicit Motion of Inconsistency in Op...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Wang, Mengfei Shi, Wenjun Zhu, Dongchen Wang, Lei Li, Jiamao Bionic Vision System Laboratory State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9783031781124

Due to the limitation of training datasets and global motion understanding to optical flow estimation, current methods only focus on local clues and ignore the motion continuity of consecutive frames, resulting in an inconsistent motion problem. After theoretical analysis, we find the multi-frame methods need to pay more attention to the continuity between cost volumes than two-frame methods. Thus, our method is based on a multi-frame framework and introduces extra object coordinates in each frame by the segmentation model to revise the matching pairs in cost volume. Specifically, we introduce a Cost Volume Adaptation Module, including a Bbox Spatial Queries to store coordinates information and a Correlation Query Queue to query the object position of different frames. On the Sintel and KITTI test benchmark, our proposed MemoFlow achieves 1.00 and 1.69 average endpoint error (AEPE) on the clean and final passes and an F1-all error of 4.43%, ranking 1st among all three-frame methods and two-frame methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Optical correlation

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