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Coexistence of antiferromagnetism and unconventional superconductivity in a quasi-one-dimensional flat-band system:Creutz lattice

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Chinese Physics B 2024年第3期33卷 583-588页

作者：徐峰张磊 School of Physics and telecommunication engineering Shaanxi University of TechnologyHanzhong 723001China

We study the coexistence of antiferromagnetism and unconventional superconductivity on the Creutz lattice which shows strictly flat bands in the noninteracting *** famous renormalized mean-field theory is used to deal with strong electron-electron repulsive Hubbard interaction in the effective low-energy t-J model,the superfluid weight of the unconventional superconducting state has been calculated via the linear response *** unconventional superconducting state with both spin-singlet and staggered spin-triplet pairs emerges beyond a critical antiferromagnetic coupling interaction,while antiferromagnetism accompanies this *** superconducting state with only spin-singlet pairs is dominant with paramagnetic *** A phase is analogous to the pseudogap phase,which shows that electrons go to form pairs but do not cause a *** also show the superfluid behavior of the unconventional superconducting state and its critical *** is proven directly that the flat band can effectively raise the critical temperature of *** is implementable to simulate and control strongly-correlated electrons'behavior on the Creutz lattice in the ultracold atoms experiment or other artificial *** results may help the understanding of the interplay between unconventional superconductivity and magnetism.

关键词： flat-band unconventional superconductivity antiferromagnetism strong electron-electron interaction superfluid weight

A Fast Insertion Tabu Search with Conflict-Avoidance Heuristic for the Multisatellite Multimode Crosslink Scheduling Problem

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Tsinghua Science and Technology 2024年第3期29卷 843-862页

作者： Weiyi Yang Lei He Xiaolu Liu Weican Meng Yingwu Chen College of Systems engineering National University of Defense TechnologyChangsha 410000China Beijing Institude of Tranking and telecommunication Technology Beijing 100000China

An agile earth-observing satellite equipped with multimode cameras capable of transmitting observation data to other satellites is developed to rapidly respond to requests with multiple observation *** gives rise to the Multisatellite Multimode Crosslink Scheduling(MMCS)problem,which involves allocating observation requests to agile satellites,selecting appropriate timing and observation modes for the requests,and transmitting the data to the ground station via the satellite communication ***,a mixed integer programming model is introduced to include all complex time and operation *** solve the MMCS problem,a two-stage heuristic method,called Fast insertion Tabu Search with Conflict-avoidance(FTS-C)heuristic,is *** the first stage,a conflict-avoidance insertion algorithm is designed to generate a high-quality initial solution by considering the requests transmission and ***,the tabu search-based second stage optimizes the initial ***,an extensive empirical study based on a real-world situation demonstrates that FTS-C can generate a solution with higher quality in less time than other state-of-the-art algorithms and the CPLEX solver.

关键词： earth observation satellites scheduling tabu search heuristic data transmission and download mixedinteger programming model

Multiscale Fusion Transformer Network for Hyperspectral Image Classification

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Journal of Beijing Institute of Technology 2024年第3期33卷 255-270页

作者： Yuquan Gan Hao Zhang Chen Yi School of telecommunication and Information engineering Xi’an University of Posts and TelecommunicationsXi’an 710121China

Convolutional neural network(CNN)has excellent ability to model locally contextual ***,CNNs face challenges for descripting long-range semantic features,which will lead to relatively low classification accuracy of hyperspectral *** address this problem,this article proposes an algorithm based on multiscale fusion and transformer network for hyperspectral image ***,the low-level spatial-spectral features are extracted by multi-scale residual ***,an attention module is introduced to focus on the more important spatialspectral ***,high-level semantic features are represented and learned by a token learner and an improved transformer *** proposed algorithm is compared with six classical hyperspectral classification algorithms on real hyperspectral *** experimental results show that the proposed algorithm effectively improves the land cover classification accuracy of hyperspectral images.

关键词： hyperspectral image land cover classification multi-scale transformer

Emotion Detection Using ECG Signals and a Lightweight CNN Model

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Computer Systems Science & engineering 2024年第5期48卷 1193-1211页

作者： Amita U.Dessai Hassanali G.Virani Department of Electronics and telecommunication engineering Goa College of EngineeringGoa UniversityPonda403401India

Emotion recognition is a growing field that has numerous applications in smart healthcare systems and Human-Computer Interaction(HCI).However,physical methods of emotion recognition such as facial expressions,voice,and text data,do not always indicate true emotions,as users can falsify *** the physiological methods of emotion detection,Electrocardiogram(ECG)is a reliable and efficient way of detecting ***-enabled smart bands have proven effective in collecting emotional data in uncontrolled *** use deep machine learning techniques for emotion recognition using ECG signals,but there is a need to develop efficient models by tuning the ***,most researchers focus on detecting emotions in individual settings,but there is a need to extend this research to group settings aswell since most of the emotions are experienced in *** this study,we have developed a novel lightweight one dimensional(1D)Convolutional Neural Network(CNN)model by reducing the number of convolution,max pooling,and classification *** optimization has led to more efficient emotion classification using *** tested the proposed model’s performance using ECG data from the AMIGOS(A Dataset for Affect,Personality and Mood Research on Individuals andGroups)dataset for both individual and group *** results showed that themodel achieved an accuracy of 82.21%and 85.62%for valence and arousal classification,respectively,in individual *** group settings,the accuracy was even higher,at 99.56%and 99.68%for valence and arousal classification,*** reducing the number of layers,the lightweight CNNmodel can process data more quickly and with less complexity in the hardware,making it suitable for the implementation on the mobile phone devices to detect emotions with improved accuracy and speed.

关键词： Emotions AMIGOS ECG lightweight 1D CNN

Dynamic properties of rumor propagation model induced by L´evy noise on social networks

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Chinese Physics B 2024年第9期33卷 223-237页

作者： Ying Jing Youguo Wang Qiqing Zhai Xianli Sun School of Science Nanjing University of Posts and TelecommunicationsNanjing 210023China School of telecommunication and Information engineering Nanjing University of Posts and TelecommunicationsNanjing 210023China

Social networks are inevitably subject to disruptions from the physical world,such as sudden internet outages that sever local connections and impede information *** Gaussian white noise,commonly used to simulate stochastic disruptions,only fluctuates within a narrow range around its mean and fails to capture large-scale variations,L´evy noise can effectively compensate for this ***,a susceptible–infected–removed rumor propagation model with L´evy noise is constructed on homogeneous and heterogeneous networks,***,the existence of a global positive solution and the asymptotic path-wise of the solution are derived on heterogeneous networks,and the sufficient conditions of rumor extinction and persistence are ***,theoretical results are verified through numerical calculations and the sensitivity analysis related to the threshold is conducted on the model *** simulation experiments on Watts–Strogatz(WS)and Barab´asi–Albert networks,it is found that the addition of noise can inhibit the spread of rumors,resulting in a stochastic resonance phenomenon,and the optimal noise intensity is obtained on the WS *** validity of the model is verified on three real datasets by particle swarm optimization algorithm.

关键词： rumor propagation model L´evy noise extinction and persistence stochastic resonance

Reinforcement learning based adaptive control for uncertain mechanical systems with asymptotic tracking

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Defence Technology（防务技术） 2024年第4期34卷 19-28页

作者： Xiang-long Liang Zhi-kai Yao Yao-wen Ge Jian-yong Yao School of Mechanical engineering Nanjing University of Science and TechnologyNanjing210094China College of Automation&College of Artificial Intelligence Nanjing University of Post and TelecommunicationNanjing210023China

This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange *** considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and *** these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become *** by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical *** approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control *** from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control *** developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output ***,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.

关键词： Adaptive control Reinforcement learning Uncertain mechanical systems Asymptotic tracking

Exciton-polaritons in a 2D hybrid organic-inorganic perovskite microcavity with the presence of optical Stark effect

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Chinese Physics B 2024年第3期33卷 551-555页

作者： Kenneth Coker 郑楚媛 Joseph Roger Arhin Kwame Opuni-Boachie Obour Agyekum 张伟利 School of Information and Communication engineering University of Electronic Science and Technology of ChinaChengdu 611731China Department of Electrical and Electronic engineering Ho Technical UniversityHo 00233Ghana telecommunication engineering Department Kwame Nkrumah University of Science and TechnologyKumasi 00233Ghana

This study investigates the properties of exciton-polaritons in a two-dimensional(2D)hybrid organic-inorganic perovskite microcavity in the presence of optical Stark *** both steady and dynamic state analyses,strong coupling between excitons of perovskite and cavity photons is revealed,indicating the formation of polaritons in the perovskite ***,it is found that an external optical Stark pulse can induce energy shifts of excitons proportional to the pulse intensity,which modifies the dispersion characteristics of the polaritons.

关键词： exciton-polaritons perovskite microcavity optical Stark effect

An Embedded Consensus ADMM Distribution Algorithm Based on Outer Approximation for Improved Robust State Estimation of Networked

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1217-1226页

作者： Zifeng Zhang Yuntao Ju State Grid Information&telecommunication Group Co. Ltd.Beijing BranchBejingChina School of Electrical and Control engineering North China University of TechnologyBeijingChina

Networked microgrids(NMGs)are critical in theaccommodation of distributed renewable ***,theexisting centralized state estimation(SE)cannot meet the demandsof NMGs in distributed energy *** currentestimator is also not robust against bad *** study introducesthe concepts of relative error to construct an improvedrobust SE(IRSE)optimization model with mixed-integer nonlinearprogramming(MINLP)that overcomes the disadvantage ofinaccurate results derived from different measurements whenthe same tolerance range is considered in the robust SE(RSE).To improve the computation efficiency of the IRSE optimizationmodel,the number of binary variables is reduced based on theprojection statistics and normalized residual methods,which effectivelyavoid the problem of slow convergence or divergenceof the algorithm caused by too many integer ***,an embedded consensus alternating direction of multiplier method(ADMM)distribution algorithm based on outer approximation(OA)is proposed to solve the IRSE optimization *** algorithm can accurately detect bad data and obtain SE resultsthat communicate only the boundary coupling informationwith *** tests show that the proposed algorithmeffectively detects bad data,obtains more accurate SE results,and ensures the protection of private information in all microgrids.

关键词： Distributed optimization alternating direction of multiplier methods(ADMM) robust state estimation(RSE) mixed-integer nonlinear programming(MINLP) networked microgrid(NMG)

Automatically identifying imperfections and attacks in practical quantum key distribution systems via machine learning

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Science China(Information Sciences) 2024年第10期67卷 359-372页

作者： Jiaxin XU Xiao MA Jingyang LIU Chunhui ZHANG Hongwei LI Xingyu ZHOU Qin WANG Institute of Quantum Information and Technology Nanjing University of Posts and Telecommunications telecommunication and Networks National Engineering Research CenterNanjing University of Posts and Telecommunications Henan Key Laboratory of Quantum Information and Cryptography Strategic Support Force Information Engineering University

The realistic security of quantum key distribution(QKD) systems is currently a hot research topic in the field of quantum communications. There are always defects in practical devices, and eavesdroppers can make use of the security risk points of various devices to obtain key information. To date, current types of security analysis tend to analyze each security risk point individually, thereby posing great challenges for the overall security evaluation of QKD systems. In this paper, for the first time, we employ machine learning algorithms to identify the defects of different devices and certain attacks in real time, with an accuracy of 98%. It provides a novel solution for the practical security evaluation of QKD systems, thereby addressing the bottleneck problem of multiple risk points being difficult to address simultaneously in QKD systems,thus paving the way for the future large-scale application of quantum communication networks.

关键词： quantum key distribution device imperfections eavasdropping attacks real-time detection machine learning algorithms

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