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Wide-angle giant photonic spin Hall effect

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Physical Review B 2022年第7期106卷 075409-075409页

作者： Zhihao Chen Yu Chen Yaodong Wu Xinxing Zhou Handong Sun Tony Low Hongsheng Chen Xiao Lin Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Synergetic Innovation Center for Quantum Effects and Applications School of Physics and Electronics Hunan Normal University Changsha 410081 China International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Engineering Technology Research Center for 2D Material Information Function Devices and Systems of Guangdong Province Institute of Microscale Optoelectronics Shenzhen University Shenzhen 518060 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore Centre for Disruptive Photonic Technologies (CDPT) School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore Department of Electrical and Computer Engineering University of Minnesota Minneapolis Minnesota 55455 USA Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China International Joint Innovation Center ZJU-UIUC Institute The Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China

The photonic spin Hall effect is a manifestation of the spin-orbit interaction of light and can be measured by a transverse shift δ of photons with opposite spins. The precise measurement of transverse shifts can enable many spin-related applications, such as precise metrology and optical sensing. However, this transverse shift is generally small (i.e., δ/λ<10−1, where λ is the wavelength), which impedes its precise measurement. To date, proposals to generate a giant spin Hall effect (namely, with δ/λ>102) have severe limitations, particularly its occurrence only over a narrow angular cone (with a width of Δθ<1∘). Here we propose a universal scheme to realize the wide-angle giant photonic spin Hall effect with Δθ>70∘ by exploiting the interface between free space and uniaxial epsilon-near-zero media. The underlying mechanism is ascribed to the almost-perfect polarization splitting between s and p polarized waves at the designed interface. Remarkably, this almost-perfect polarization splitting does not resort to the interference effect and is insensitive to the incident angle, which then gives rise to the wide-angle giant photonic spin Hall effect.

关键词： Light-matter interaction Photonics Spin Hall effect Spin-orbit coupling

Demonstration of broadband topological slow light

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arXiv 2022年

作者： Chen, Fujia Xue, Haoran Pan, Yuang Wang, Maoren Hu, Yuanhang Zhang, Li Chen, Qiaolu Han, Song Liu, Gui-Geng Gao, Zhen Zhou, Peiheng Yin, Wenyan Chen, Hongsheng Zhang, Baile Yang, Yihao Interdisciplinary Center for Quantum Information State Key Lab. of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China ZJU-Hangzhou Global Science and Technology Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang ZJU-UIUC Institute Zhejiang University Hangzhou310027 China Jinhua Institute of Zhejiang University Zhejiang University Jinhua321099 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore637371 Singapore Centre for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore National Engineering Research Center of Electromagnetic Radiation Control Materials State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of China Chengdu610054 China Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China

Slow-light devices are able to significantly enhance light-matter interaction due to the reduced group velocity of light, but a very low group velocity is usually achieved in a narrow bandwidth, accompanied by extreme sensitivity to imperfections that causes increased disorder-induced attenuation. Recent theories have suggested an ideal solution to this problem—unidirectional chiral photonic states, previously discovered in structures known as photonic topological insulators, not only resist backscattering from imperfections but can also be slowed down in the entire topological bandgap with multiple windings in the Brillouin zone. Here, we report on the experimental demonstration of broadband topological slow light in a photonic topological insulator. When coupled with periodic resonators that form flat bands, the chiral photonic states can wind many times around the Brillouin zone, achieving an ultra-low group velocity in the entire topological bandgap. This demonstration extends the scope of topological photonics into slow light engineering, and opens a unique avenue in the dispersion manipulation of chiral photonic states. © 2022, CC BY.

关键词： Slow light

Dynamical primal-dual accelerated method with applications to network optimization

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arXiv 2019年

作者： Zeng, Xianlin Lei, Jinlong Chen, Jie Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Department of control science and engineering Tongji University Shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China

This paper develops a continuous-time primal-dual accelerated method with an increasing damping coefficient for a class of convex optimization problems with affine equality constraints. We then analyze critical values for parameters in the proposed method and prove that the rate of convergence is O(t12 ) by choosing proper parameters. As far as we know, this is the first continuous-time primal-dual accelerated method that can obtain the optimal rate. Then this work applies the proposed method to two network optimization problems, a distributed optimization problem with consensus constraints and a distributed extended monotropic optimization problem, and obtains two variant distributed algorithms. Finally, numerical simulations are given to demonstrate the efficacy of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Continuous time systems

Multi-modal digital twins for industrial anomaly detection: Framework, method, and application

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Robotics and Computer-Integrated Manufacturing 2026年 97卷

作者： Cheng Ren Ming Li Cailian Chen Xinping Guan George Q. Huang Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hung Hom Hong Kong China Key Laboratory of System Control and Information Processing Department of Automation Shanghai Jiao Tong University Shanghai China Research Institute for Advanced Manufacturing The Hong Kong Polytechnic University Hung Hom Hong Kong China Collaborative Generative AI (Co-GenAI) Research Centre The Hong Kong Polytechnic University Hung Hom Hong Kong China Research Centre for Digital Transformation of Tourism The Hong Kong Polytechnic University Hung Hom Hong Kong China Centre for Transformative Garment Production Hong Kong Science Park Pak Shek Kok Hong Kong China

Anomaly detection plays a key role in maintaining the reliable and stable operation of industrial systems, especially in high-reliability fields. Conventional single-modal data cannot provide comprehensive information about the detected object, resulting in false or missed detection. To address the challenges of complex anomaly patterns and heterogeneous data in industrial scenarios, we propose MMDT-IAD, a multi-modal digital twin (DT)-based anomaly detection framework that integrates edge–cloud collaboration. By lever- aging physical, geometric, visual, and semantic modalities, MMDT-IAD constructs a comprehensive virtual representation of monitored objects and enables real-time, scalable detection across distributed industrial environments. Next, to enable efficient fusion of heterogeneous DT modalities, we propose a One-Primary- Three-Auxiliary (1P3A) cross-modal decision fusion strategy. Finally, we apply the MMDT-IAD frame-work to the anomaly detection of aviation electrical connector pins, and present a detailed application process. The experimental results prove the effectiveness of the MMDT-IAD framework in detecting abnormal pins. Moreover, we discuss the generality of MMDT-IAD framework considering several common industrial anomalies. These results highlight the potential of MMDT-IAD framework and 1P3A method to significantly improve anomaly detection in other complex industrial scenarios.

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Wide-angle giant photonic spin Hall effect

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arXiv 2022年

作者： Chen, Zhihao Chen, Yu Wu, Yaodong Zhou, Xinxing Sun, Handong Low, Tony Chen, Hongsheng Lin, Xiao Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control Ministry of Education Synergetic Innovation Center for Quantum Effects and Applications School of Physics and Electronics Hunan Normal University Changsha410081 China International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Engineering Technology Research Center for 2D Material Information Function Devices and Systems of Guangdong Province Institute of Microscale Optoelectronics Shenzhen University Shenzhen518060 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China International Joint Innovation Center ZJU-UIUC Institute The Electromagnetics Academy at Zhejiang University Zhejiang University Haining314400 China

Photonic spin Hall effect is a manifestation of spin-orbit interaction of light and can be measured by a transverse shift δ of photons with opposite spins. The precise measurement of transverse shifts can enable many spin-related applications, such as precise metrology and optical sensing. However, this transverse shift is generally small (i.e. δ/λ -1, λ is the wavelength), which impedes its precise measurement. To-date proposals to generate giant spin Hall effect (namely with δ/λ > 102) have severe limitations, particularly its occurrence only over a narrow angular cone (with a width of ∆0 70◦ by exploiting the interface between free space and uniaxial epsilon-near-zero media. The underlying mechanism is ascribed to the almost-perfect polarization splitting between s and p polarized waves at the designed interface. Remarkably, this almost-perfect polarization splitting does not resort to the interference effect and is insensitive to the incident angle, which then gives rise to the wide-angle giant photonic spin Hall effect. Copyright © 2022, The Authors. All rights reserved.

关键词： Polarization

Corrigendum to “T2V_TF: An adaptive timing encoding mechanism based transformer with multi-source heterogeneous information fusion for portfolio management: A case of the Chinese A50 stocks” [Expert Syst. Appl. 213 (2023) 119020]

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Expert systems with Applications 2024年 239卷

作者： Feng Zhou Qun Zhang Yuan Zhu Tian Li School of Information Sciences Guangdong University of Finance and Economics Guangzhou 510320 China School of Finance Guangdong University of Foreign Studies Guangzhou Guangdong 510006 China Southern China Institute of Fortune Management Guangzhou Guangdong 510006 China Institute of Financial Openness and Asset Management Guangzhou Guangdong 510006 China School of Automation China University of Geosciences Wuhan Hubei 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan Hubei 430074 China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Shanghai 200433 China Department of Finance School of Business The Chinese University of Hong Kong Shatin NT Hong Kong

Deep learning radiomics for assessment of gastroesophageal varices in people with compensated advanced chronic liver disease

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arXiv 2023年

作者： Wang, Lan He, Ruiling Zhao, Lili Wang, Jia Geng, Zhengzi Ren, Tao Zhang, Guo Zhang, Peng Tang, Kaiqiang Gao, Chaofei Chen, Fei Zhang, Liting Zhou, Yonghe Li, Xin He, Fanbin Huan, Hui Wang, Wenjuan Liang, Yunxiao Tang, Juan Ai, Fang Wang, Tingyu Zheng, Liyun Zhao, Zhongwei Ji, Jiansong Liu, Wei Xu, Jiaojiao Liu, Bo Wang, Xuemei Zhang, Yao Yan, Qiong Lv, Muhan Chen, Xiaomei Zhang, Shuhua Wang, Yihua Liu, Yang Yin, Li Liu, Yanni Huang, Yanqing Liu, Yunfang Wang, Kun Su, Meiqin Bian, Li An, Ping Zhang, Xin Qian, Linxue Li, Shao Qi, Xiaolong Institute for TCM-X MOE Key Laboratory of Bioinformatics Bioinformatics Division BNRIST Department of Automation Tsinghua University Beijing China Department of Ultrasound Donggang Branch the First Hospital of Lanzhou University Lanzhou China The First Clinical Medical College of Lanzhou University Lanzhou China Department of Gastroenterology and Hepatology Tianjin Second People's Hospital Tianjin China Department of Ultrasound Beijing Friendship Hospital Capital Medical University Beijing China Department of Ultrasound The People's Hospital of Linxia Linxia China Department of Gastroenterology Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region Sichuan China Department of Gastroenterology The People's Hospital of Guangxi Zhuang Autonomous Region Nanning China Department of Control and Systems Engineering Nanjing University Nanjing China Department of Ultrasound The First Hospital of Lanzhou University Lanzhou China Department of Infectious Diseases The First Hospital of Lanzhou University Lanzhou China Department of Ultrasonography Tianjin Second People's Hospital Tianjin China Department of Infectious Disease Zigong First People's Hospital Zigong China Department of Ultrasound Zigong First People's Hospital Zigong China Department of Gastroscopy Zigong First People's Hospital Zigong China Department of Radiology Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research Fifth Affiliated Hospital of Wenzhou Medical University Lishui China Ultrasound Diagnosis Center Shaanxi Provincial People's Hospital Xi'An China Department of Ultrasound Ditan Hospital Capital Medical University Beijing China Department of Gastroenterology The Affiliated Hospital of Southwest Medical University Luzhou China Department of Ultrasound The Affiliated Hospital of Southwest Medical University Luzhou China Department of Ultrasound North China University of Science and Technology Affiliated Hospital Tangshan China Depar

Objective: Bleeding from gastroesophageal varices (GEV) is a medical emergency associated with high mortality. We aim to construct an artificial intelligence-based model of two-dimensional shear wave elastography (2D-SWE) of the liver and spleen to precisely assess the risk of GEV and high-risk gastroesophageal varices (HRV). Design: A prospective multicenter study was conducted in patients with compensated advanced chronic liver disease. 305 patients were enrolled from 12 hospitals, and finally 265 patients were included, with 1136 liver stiffness measurement (LSM) images and 1042 spleen stiffness measurement (SSM) images generated by 2D-SWE. We leveraged deep learning methods to uncover associations between image features and patient risk, and thus conducted models to predict GEV and HRV. Results: A multi-modality Deep Learning Risk Prediction model (DLRP) was constructed to assess GEV and HRV, based on LSM and SSM images, and clinical information. Validation analysis revealed that the AUCs of DLRP were 0.91 for GEV (95% CI 0.90 to 0.93, p Copyright © 2023, The Authors. All rights reserved.

关键词： Deep learning

Exponentially convergent distributed Nash equilibrium seeking for constrained aggregative games

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arXiv 2019年

作者： Liang, Shu Yi, Peng Hong, Yiguang Peng, Kaixiang Department of Control Science & Engineering Tongji University Shanghai200092 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai201210 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China

Distributed Nash equilibrium seeking of aggregative games is investigated and a continuous-time algorithm is proposed. The algorithm is designed by virtue of projected gradient play dynamics and distributed average tracking dynamics, and is applicable to games with constrained strategy sets and weight-balanced communication graphs. We obtain an exponential convergence of the proposed algorithm to the Nash equilibrium. Numerical examples illustrate the effectiveness of our methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Game theory

Decision-Making in Driver-automation Shared control: A Review and Perspectives

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arXiv 2020年

作者： Wang, Wenshuo Na, Xiaoxiang Cao, Dongpu Gong, Jianwei Xi, Junqiang Xing, Yang Wang, Fei-Yue CA94720 United States Department of Engineering University of Cambridge Trumpington Street CambridgeCB2 1PZ United Kingdom Mechanical and Mechatronics Engineering University of Waterloo 200 University Ave. West Waterloo ONN2L3G1 Canada Department of Mechanical Engineering Beijing Institute of Technology Beijing100081 China School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore639798 Singapore State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

Shared control schemes allow a human driver to work with an automated driving agent in driver-vehicle systems while retaining the driver’s abilities to control. The human driver, as an essential agent in the driver-vehicle shared control systems, should be precisely modeled regarding their cognitive processes, control strategies, and decision-making processes. The interactive strategy design between drivers and automated driving agents brings an excellent challenge for human-centric driver assistance systems due to the inherent characteristics of humans. Many open-ended questions arise, such as what proper role of human drivers should act in a shared control scheme? How to make an intelligent decision capable of balancing the benefits of agents in shared control systems? Due to the advent of these attentions and questions, it is desirable to present a survey on the decision-making between human drivers and highly automated vehicles, to understand their architectures, human driver modeling, and interaction strategies under the driver-vehicle shared schemes. Finally, we give a further discussion on the key future challenges and opportunities. They are likely to shape new potential research directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Decision making