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Exploring parity magnetic effects through quantum simulation with superconducting qubits

Physical Review Applied 2024年第3期21卷 034052-034052页

作者： Yu Zhang Yan-Qing Zhu Jianwen Xu Wen Zheng Dong Lan Giandomenico Palumbo Nathan Goldman Shi-Liang Zhu Xinsheng Tan Z.D. Wang Yang Yu National Laboratory of Solid State Microstructures School of Physics Nanjing University Nanjing 210093 China Shishan Laboratory Suzhou Campus of Nanjing University Suzhou 215000 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Department of Physics and HK Institute of Quantum Science & Technology The University of Hong Kong Pokfulam Road Hong Kong China Hefei National Laboratory Hefei 230088 China School of Theoretical Physics Dublin Institute for Advanced Studies 10 Burlington Road Dublin 4 Ireland Center for Nonlinear Phenomena and Complex Systems Université Libre de Bruxelles CP 231 Campus Plaine Brussels B-1050 Belgium Key Laboratory of Atomic and Subatomic Structure and Quantum Control (Ministry of Education) School of Physics South China Normal University Guangzhou 510006 China Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials Guangdong-Hong Kong Joint Laboratory of Quantum Matter South China Normal University Guangzhou 510006 China

We present a successful realization of four-dimensional semimetal bands featuring tensor monopoles, achieved using superconducting quantum circuits. Our experiment involves the creation of a highly tunable diamond energy diagram with four coupled transmons, and the parametric modulation of their tunable couplers, effectively mapping momentum space to parameter space. This approach enables us to establish a four-dimensional Dirac-like Hamiltonian with fourfold degenerate points. Moreover, we manipulate the energy of tensor monopoles by introducing an additional pump microwave field, generating effective magnetic and pseudoelectric fields and simulating topological parity magnetic effects emerging from the parity anomaly. Utilizing nonadiabatic response methods, we measure the fractional second Chern number for a Dirac valley with a varying mass term, signifying a nontrivial topological phase transition connected to a five-dimensional Yang monopole. Our work lays the foundation for further investigations into higher-dimensional topological states of matter and enriches our comprehension of topological phenomena.

关键词： Electronic structure Quantum circuits Quantum information with solid state qubits Quantum simulation Topological phases of matter Dirac semimetal Magnetic monopoles Superconducting qubits

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An Intelligent Maritime Scene Frame Prediction Based on Digital Twins Technology

An Intelligent Maritime Scene Frame Prediction Based on Digi...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Zhong-Zheng Guo Kai Wang Jiang-Yi Qin Xian-Bin Li De-Chao Ran Yu Shen Unmanned Systems Research Center National Innovation Institute of Defense Technology Academy of Military Science Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

This paper proposes a scene frame prediction system based on digital twin technology. The system is mainly composed of an unmanned perception module, a communication link module, a command center module that provides intelligent computing services, and an interaction and visualization module for human operators. These modules together constitute a system for predicting and recovery the time-series matrix composed of scene frames and object frames. At the same time, in view of the current problems of lack of real-time information and long response time in the maritime search and rescue (SAR) field, this paper instantiates the above system to improve the existing SAR system. Satellites and unmanned vehicles perceive part of the scene data of the real cyber-physical system in real-time and divide them into multiple frames according to the timestamps. In addition, this paper also proposes an environmental graph-attention network (Env-GAT) to achieve efficient and reliable frame predicting. Finally, this paper verifies that the performance of the spatiotemporal attention graph network model has reached the optimal level through computational experiments.

关键词： Satellites Digital twin Conferences Unmanned vehicles Search problems Real-time systems Trajectory

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Guidance control for Parallel Parking Tasks

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IEEE/CAA Journal of Automatica Sinica 2020年第1期7卷 301-306页

作者： Jiyuan Tan Chunling Xu Li Li Fei-Yue Wang Dongpu Cao Lingxi Li Key Laboratory of Urban Intelligent Traffic Control Technology North China University of TechnologyBeijing 100144China Beijing Transport Institute Beijing 100073China Department of Automation BNRistTsinghua UniversityBeijing 100084China Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100080China Driver Cognition and Automated Driving Laboratory University of WaterlooWaterloo N2L 3G1Canada Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndiana 46202-5132 USA

Parking into small berths remains difficult for unskilled drivers. Researchers had proposed different automatic parking systems to solve this problem. The first kind of strategies(called parking trajectory planning) designs a detailed reference trajectory that links the start and ending points of a special parking task and let the vehicle track this reference trajectory so as to park into the berth. The second kind of strategies(called guidance control) just characterizes several regimes of driving actions as well as the important switching points in certain rule style and let the vehicle follows the pre-selected series of actions so as to park into the berth. Parking guidance control is simpler than parking trajectory planning. However, no studies thoroughly validated parking guidance control before. In this paper, a new automatic parking method is presented, which could characterize the desired control actions directly. Then the feasibility is examined carefully. Tests show that a simple parking guidance control strategy can work in most parallel parking tasks, if the available parking berth is not too small. This finding helps to build more concise automatic parking systems that can efficiently guide human drivers.

关键词： Automatic parking guidance control trajectory planning

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Learning regional attention convolutional neural network for motion intention recognition based on EEG data 29

Learning regional attention convolutional neural network for...

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29th International Joint Conference on Artificial Intelligence, IJCAI 2020

作者： Fang, Zhijie Wang, Weiqun Ren, Shixin Wang, Jiaxing Shi, Weiguo Liang, Xu Fan, Chen-Chen Hou, Zengguang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology Beijing China

ISBN: (纸本)9780999241165

Recent deep learning-based Brain-Computer Interface (BCI) decoding algorithms mainly focus on spatial-temporal features, while failing to explicitly explore spectral information which is one of the most important cues for BCI. In this paper, we propose a novel regional attention convolutional neural network (RACNN) to take full advantage of spectral-spatial-temporal features for EEG motion intention recognition. Time-frequency based analysis is adopted to reveal spectral-temporal features in terms of neural oscillations of primary sensorimotor. The basic idea of RACNN is to identify the activated area of the primary sensorimotor adaptively. The RACNN aggregates a varied number of spectral-temporal features produced by a backbone convolutional neural network into a compact fixed-length representation. Inspired by the neuroscience findings that functional asymmetry of the cerebral hemisphere, we propose a region biased loss to encourage high attention weights for the most critical regions. Extensive evaluations on two benchmark datasets and real-world BCI dataset show that our approach significantly outperforms previous methods. © 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.

关键词： Brain computer interface

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Semi-supervised Long-tail Endoscopic Image Classification

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Chinese Medical Sciences Journal 2022年第3期37卷 171-180,I0002页

作者： Runnan Cao Mengjie Fang Hailing Li Jie Tian Di Dong School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular Imagingthe State Key Laboratory of Management and Control for Complex SystemsInstitute of AutomationChinese Academy of SciencesBeijing 100190China Beijing Advaneed Innovation Center for Big Data-Based Precision Medicine School of Engineering MedicineBeihang UniversityBeijing 100191China Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education School of Life Science and TechnologyXidian UniversityXi'an 710126China

Objective To explore the semi-supervised learning(SSL) algorithm for long-tail endoscopic image classification with limited *** We explored semi-supervised long-tail endoscopic image classification in HyperKvasir,the largest gastrointestinal public dataset with 23 diverse ***-supervised learning algorithm FixMatch was applied based on consistency regularization and *** splitting the training dataset and the test dataset at a ratio of 4:1,we sampled 20%,50%,and 100% labeled training data to test the classification with limited *** The classification performance was evaluated by micro-average and macro-average evaluation metrics,with the Mathews correlation coefficient(MCC) as the overall *** algorithm improved the classification performance,with MCC increasing from 0.8761 to 0.8850,from 0.8983 to 0.8994,and from 0.9075 to 0.9095 with 20%,50%,and 100% ratio of labeled training data,*** a 20% ratio of labeled training data,SSL improved both the micro-average and macro-average classification performance;while for the ratio of 50% and 100%,SSL improved the micro-average performance but hurt macro-average *** analyzing the confusion matrix and labeling bias in each class,we found that the pseudo-based SSL algorithm exacerbated the classifier’ s preference for the head class,resulting in improved performance in the head class and degenerated performance in the tail *** SSL can improve the classification performance for semi-supervised long-tail endoscopic image classification,especially when the labeled data is extremely limited,which may benefit the building of assisted diagnosis systems for low-volume ***,the pseudo-labeling strategy may amplify the effect of class imbalance,which hurts the classification performance for the tail class.

关键词： endoscopic image artificial intelligence semi-supervised learning long-tail distribution image classification

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Approximate optimal control of nonlinear systems with mismatched perturbations based on asymptotically stable critic neural network 2020

Approximate optimal control of nonlinear systems with mismat...

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6th International Conference on Computing and Data Engineering, ICCDE 2020 and 2020 International Conference on Artificial Intelligence in Electronics Engineering, AIEE 2020

作者： Zhao, Bo Hou, Jiaxu Guo, Ping Liu, Derong Xu, Yancai School of Systems Science Beijing Normal University Beijing100875 China School of Automation Guangdong University of Technology Guangzhou510006 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781450376730

In this paper, the approximate optimal control problem for nonlinear systems with mismatched perturbations is addressed through asymptotically stable critic neural network (NN). By employing the estimated perturbation via nonlinear perturbation observer, the online updated value function is constructed to reflect the real-time perturbations, regulation and control simultaneously. In order to solve the Hamilton-Jacobi-Bellman equation, an asymptotically stable critic NN is established based on the novel nested update laws. Thus, the approximate optimal control is obtained to guarantee the closed-loop system to be uniformly ultimately bounded based on the Lyapunov's direct method. Simulation results illustrate the effectiveness of the developed control scheme. © 2020 ACM International Conference Proceeding Series. All rights reserved.

关键词： Reinforcement learning

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Realization of a Data-based Adaptive Networked Tracking control in NetCon System

Realization of a Data-based Adaptive Networked Tracking Cont...

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第40届中国控制会议

作者： Ye Zhao Shiwen Tong College of Urban Rail Transit and Logistics Beijing Union University College of Robotics Beijing Union University State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of Sciences

It is very difficult to realize the networked tracking control of a controlled process with unclear mechanism. An adaptive networked tracking control method that we proposed can solve such a problem. The method is a data-based control scheme started from the input-output data of the controlled process. We have realized it in the NetCon system. Firstly, the T-S fuzzy model of the controlled object is established according to input-output data by using fuzzy cluster modeling *** the fuzzy prediction model is obtained by transforming it into the fuzzy singleton model through equivalent transformation.A series of control actions are derived by inverting the fuzzy singleton model according to the reversibility condition. These predicted values can compensate the data dropout and time delay in the network communication channels. The influence of external disturbance and uncertainty on system performance is eliminated by using internal model structure and adaptive control method. Finally, experiment results in NetCon system show the effectiveness of the proposed method.

关键词： Fuzzy singleton model inverse model adaptive strategy NetCon system

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A Knowledge Enhanced Learning and Semantic Composition Model for Multi-Claim Fact Checking

arXiv

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arXiv 2021年

作者： Wang, Shuai Wei, Penghui Kong, Qingchao Mao, Wenji State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

To inhibit the spread of rumorous information and its severe consequences, traditional fact checking aims at retrieving relevant evidence to verify the veracity of a given claim. Fact checking methods typically use knowledge graphs (KGs) as external repositories and develop reasoning mechanism to retrieve evidence for verifying the triple claim. However, existing methods only focus on verifying a single claim. As real-world rumorous information is more complex and a textual statement is often composed of multiple clauses (i.e. represented as multiple claims instead of a single one), multi-claim fact checking is not only necessary but more important for practical applications. Although previous methods for verifying a single triple can be applied repeatedly to verify multiple triples one by one, they ignore the contextual information implied in a multi-claim statement and could not learn the rich semantic information in the statement as a whole. In this paper, we propose an end-to-end knowledge enhanced learning and verification method for multi-claim fact checking. Our method consists of two modules, KG-based learning enhancement and multi-claim semantic composition. To fully utilize the contextual information implied in multiple claims, the KG-based learning enhancement module learns the dynamic context-specific representations via selectively aggregating relevant attributes of entities. To capture the compositional semantics of multiple triples, the multi-claim semantic composition module constructs the graph structure to model claim-level interactions, and integrates global and salient local semantics with multi-head attention. We conduct experimental studies to validate our proposed method, and experimental results on a real-world dataset and two benchmark datasets show the effectiveness of our method for multi-claim fact checking over *** Codes 68T50 Copyright © 2021, The Authors. All rights reserved.

关键词： Knowledge graph

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Data Augmentation Using Image Generation for Change Detection

Data Augmentation Using Image Generation for Change Detectio...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Xuan Li Haibin Duan Hui Zhang Fei-Yue Wang Peng Cheng Laboratory Shenzhen China Beihang University Beijing China Beijing Jiaotong University Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Learning-based change detection (CD) in water scenarios is a key functionality for unmanned aerial vehicle (UAV). However, computer vision algorithms require large number of labeled datasets. Inspired by parallel intelligence, we propose a systematic framework for data generation. In this work, the framework consists of simulated scene and image generation network. In simulated scene, simulated images with pixel-level annotations are automatically generated. Then, image generation network uses paired images (real and simulated) to generate synthetic images. We use simulated and synthetic images in combination with publicly available real-world images to conduct experiments. The experimental results indicate that: 1) simulated images can be used in change detection research; 2) synthetic images effectively improve the performance of supervised change detection model.

关键词： Training Computer vision Systematics Image synthesis Change detection algorithms Annotations Digital twin

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Distributed adaptive stabilization

arXiv

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arXiv 2021年

作者： Sun, Zhiyong Rantzer, Anders Li, Zhongkui Robertsson, Anders Eindhoven Netherlands Department of Automatic Control Lund University Sweden State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing China

In this paper we consider distributed adaptive stabilization for uncertain multivariable linear systems with a time-varying diagonal matrix gain. We show that uncertain multivariable linear systems are stabilizable by diagonal matrix high gains if the system matrix is an H-matrix with positive diagonal entries. Based on matrix measure and stability theory for diagonally dominant systems, we consider two classes of uncertain linear systems, and derive a threshold condition to ensure their exponential stability by a monotonically increasing diagonal gain matrix. When each individual gain function in the matrix gain is updated by state-dependent functions using only local state information, the boundedness and convergence of both system states and adaptive matrix gains are guaranteed. We apply the adaptive distributed stabilization approach to adaptive synchronization control for large-scale complex networks consisting of nonlinear node dynamics and time-varying coupling weights. A unified framework for adaptive synchronization is proposed that includes several general design approaches for adaptive coupling weights to guarantee network synchronization. Copyright © 2021, The Authors. All rights reserved.

关键词： Adaptive control systems

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