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Simulating Large Quantum Circuits on a Small Quantum computer

Physical Review Letters 2020年第15期125卷 150504-150504页

作者： Tianyi Peng Aram W. Harrow Maris Ozols Xiaodi Wu Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Center for Theoretical Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA University of Amsterdam and QuSoft 1098 XG Amsterdam Netherlands Department of Computer Science Institute for Advanced Computer Studies and Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland 20742 USA

Limited quantum memory is one of the most important constraints for near-term quantum devices. Understanding whether a small quantum computer can simulate a larger quantum system, or execute an algorithm requiring more qubits than available, is both of theoretical and practical importance. In this Letter, we introduce cluster parameters K and d of a quantum circuit. The tensor network of such a circuit can be decomposed into clusters of size at most d with at most K qubits of inter-cluster quantum communication. We propose a cluster simulation scheme that can simulate any (K,d)-clustered quantum circuit on a d-qubit machine in time roughly 2O(K), with further speedups possible when taking more fine-grained circuit structure into account. We show how our scheme can be used to simulate clustered quantum systems—such as large molecules—that can be partitioned into multiple significantly smaller clusters with weak interactions among them. By using a suitable clustered ansatz, we also experimentally demonstrate that a quantum variational eigensolver can still achieve the desired performance for estimating the energy of the BeH2 molecule while running on a physical quantum device with half the number of required qubits.

关键词： Quantum algorithms Quantum simulation

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ROS-Enabled Hardware Framework for Experimental Robotics

ROS-Enabled Hardware Framework for Experimental Robotics

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2019 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2019

作者： Strohmer, Beck Bogild, Anders Sorensen, Anders Stengaard Larsen, Leon Bonde Advanced Computer Systems Group under the Faculty of Engineering University of Southern Denmark Denmark Welfare Technology Group under the Faculty of Engineering University of Southern Denmark Denmark

Applying FPGAs and real-time bare-metal code in experimental robots has many benefits but puts high demands on the skills of students and researchers. This contribution presents an interface between FPGA, hard-macro m... 详细信息

ISBN: (纸本)9781728119571

关键词： Field programmable gate arrays (FPGA)

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Structural and functional analysis of a potent human neutralizing antibody against enterovirus A71

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Science China(Life Sciences) 2022年第12期65卷 2517-2526页

作者： Zhe Chen Linlin Bao Bin Zhu Hua Fu Shuangli Zhu Tianjiao Ji Ying Xue Chuan Liu Xurong Wang Fengdi Li Qi Lv Feifei Qi Pin Yu Wei Deng Wenbo Xu Chuan Qin Hongrong Liu Qi Jin MOH Key Laboratory of Systems Biology of Pathogens Institute of Pathogen BiologyChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases NHC Key Laboratory of Human Disease Comparative MedicineInstitute of Laboratory Animal ScienceChinese Academy of Medical Sciences and Comparative Medicine CenterPeking Union Medical CollegeBeijing 100021China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China National Institute for Viral Disease Control and Prevention China CDCBeijing 102206China Ministry of Education Key Laboratory of Protein Sciences Beijing Advanced Innovation Center for Structural BiologyTsinghua UniversityBeijing 100084China Key Laboratory for Matter Microstructure and Function of Hunan Province Key Laboratory of Low-dimensional Quantum Structures and Quantum ControlSchool of Physics and ElectronicsHunan Normal UniversityChangsha 410081China Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases Hangzhou 310058China

Enterovirus A71(EV-A71) causes major outbreaks of hand,foot,and mouth disease(HFMD) in many countries,most frequently affecting children,and a small proportion of cases may lead to ***,no vaccine is available in most endemic regions,and no licenced treatments for EV-A71 infection are ***,we characterize a human monoclonal antibody(Hu MAb),E1,by screening a Fab antibody phage library derived from patients who recovered from EV-A71 infection.E1 exhibits strong neutralizing activity against EV-A71 virus in *** cryo-electron microscopy(cryo-EM) structures of the EV-A71 virion in complex with E1 Fab fragments demonstrated that E1 recognized an epitope formed by residues in the BC and HI loops of *** a mouse model,E1 effectively protected against lethal EV-A71 challenge in both prophylactic and therapeutic *** particular,E1 significantly reduces virus titers and muscle damage.E1 might represent a potential adjunct to EV-A71 treatment.

关键词： enterovirus A71 antibody mouse models cryo-electron microscopy

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AITIA: Embedded AI Techniques for Industrial Applications

AITIA: Embedded AI Techniques for Industrial Applications

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International Conference on Field Programmable Logic and Applications

作者： Marcelo Brandalero Mitko Veleski Hector Gerardo Muñoz Hernandez Muhammad Ali Laurens Le Jeune Toon Goedemé Nele Mentens Jurgen Vandendriessche Lancelot Lhoest Bruno Da Silva Abdellah Touhafi Diana Goehringer Michael Hübner Chair of Computer Engineering Brandenburg University of Technology Cottbus-Senftenberg Germany Chair of Adaptive Dynamic Systems Technische Universitaet Dresden Germany ES&S - Imec-COSIC KU Leuven Belgium EAVISE - PSI KU Leuven Belgium Leiden Institute of Advanced Computer Science Leiden University The Netherlands Vrije Universiteit Brussel Belgium Vrije Universiteit Brussel Belgium

Motivated by an increasing interest from startups in embedded Artificial Intelligence (AI) and by their limited expertise, the AITIA Project targets the development of embedded AI techniques for industrial applications. This extended abstract presents the motivation and the solutions being developed towards four use cases: smart sensors, network intrusion detection, driver-assistance systems, and Industry 4.0.

关键词： Network intrusion detection Artificial intelligence Intelligent sensors

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Probabilistic margins for instance reweighting in adversarial training 21

Probabilistic margins for instance reweighting in adversaria...

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Proceedings of the 35th International Conference on Neural Information Processing systems

作者： Qizhou Wang Feng Liu Bo Han Tongliang Liu Chen Gong Gang Niu Mingyuan Zhou Masashi Sugiyama Department of Computer Science Hong Kong Baptist University DeSI Lab Australian Artificial Intelligence Institute University of Technology Sydney TML Lab School of Computer Science Faculty of Engineering The University of Sydney PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of MoE and Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology RIKEN Center for Advanced Intelligence Project (AIP) McCombs School of Business The University of Texas at Austin RIKEN Center for Advanced Intelligence Project (AIP) and Graduate School of Frontier Sciences The University of Tokyo

ISBN: (纸本)9781713845393

Reweighting adversarial data during training has been recently shown to improve adversarial robustness, where data closer to the current decision boundaries are regarded as more critical and given larger weights. However, existing methods measuring the closeness are not very reliable: they are discrete and can take only a few values, and they are path-dependent, i.e., they may change given the same start and end points with different attack paths. In this paper, we propose three types of probabilistic margin (PM), which are continuous and path-independent, for measuring the aforementioned closeness and reweighting adversarial data. Specifically, a PM is defined as the difference between two estimated class-posterior probabilities, e.g., such a probability of the true label minus the probability of the most confusing label given some natural data. Though different PMs capture different geometric properties, all three PMs share a negative correlation with the vulnerability of data: data with larger/smaller PMs are safer/riskier and should have smaller/larger weights. Experiments demonstrated that PMs are reliable and PM-based reweighting methods outperformed state-of-the-art counterparts.

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ST-LSTM: Spatio-Temporal Graph Based Long Short-Term Memory Network For Vehicle Trajectory Prediction

ST-LSTM: Spatio-Temporal Graph Based Long Short-Term Memory ...

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IEEE International Conference on Image Processing

作者： Guangxi Chen Ling Hu Qieshi Zhang Ziliang Ren Xiangyang Gao Jun Cheng School of Computer Science and Information Security Guilin University of Electronic Technology China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

Autonomous vehicles need the ability to predict the trajectory of surrounding vehicles, so as to make a rational decision planning, improve driving safety and ride comfort. In this paper, a new hierarchical Long Short-Term Memory (LSTM) based on Spatio-Temporal (ST) graph is proposed for vehicle trajectory prediction. Our ST-LSTM uses three layers of different LSTMs to capture the information of spatial, temporal and trajectory data, and LSTM-based encoder-decoder model as a whole, which is capable of accurately predicting future trajectories for vehicles on the highway. Our model trained and validated on the publicly available NGSIM US-101 and I-80 datasets. In comparison to state-of-art methods, our method could achieve a more accurate prediction trajectory over 5s time horizon.

关键词： Trajectory Predictive models Hidden Markov models Feature extraction Data models Data mining Decoding

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Integrated Sensing and Communication from Learning Perspective: An SDP3 Approach

arXiv

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arXiv 2021年

作者： Li, Guoliang Wang, Shuai Li, Jie Wang, Rui Liu, Fan Peng, Xiaohui Han, Tony Xiao Xu, Chengzhong Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Huawei technologies Co. Ltd. Shenzhen China Department of Computer Science University of Macau China

Characterizing the sensing and communication performance tradeoff in integrated sensing and communication (ISAC) systems is challenging in the applications of learning-based human motion recognition. This is because of the large experimental datasets and the black-box nature of deep neural networks. This paper presents SDP3, a Simulation-Driven Performance Predictor and oPtimizer, which consists of SDP3 data simulator, SDP3 performance predictor and SDP3 performance optimizer. Specifically, the SDP3 data simulator generates vivid wireless sensing datasets in a virtual environment, the SDP3 performance predictor predicts the sensing performance based on the function regression method, and the SDP3 performance optimizer investigates the sensing and communication performance tradeoff analytically. It is shown that the simulated sensing dataset matches the experimental dataset very well in the motion recognition accuracy. By leveraging SDP3, it is found that the achievable region of recognition accuracy and communication throughput consists of a communication saturation zone, a sensing saturation zone, and a communication-sensing adversarial zone, of which the desired balanced performance for ISAC systems lies in the third one. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

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Lightdet: A Lightweight and Accurate Object Detection Network

Lightdet: A Lightweight and Accurate Object Detection Networ...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Qiankun Tang Jie Li Zhiping Shi Yu Hu Research Center for Intelligent Computing Systems State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing Advanced Innovation Center for Imaging Theory and Technology Capital Normal University

ISBN: (数字)9781509066315

ISBN: (纸本)9781509066322

The extensive computational burden limits the usage of accurate but complex object detectors in resource-bounded scenarios. In this paper, we present a lightweight object detector, named LightDet, to address this dilemma. We design a lightweight backbone that is able to capture rich low-level features by the proposed Detail-Preserving Module. To effectively aggregate bottom and top-down features, we introduce an efficient Feature-Preserving and Refinement Module. A lightweight prediction head is employed to further reduce the entire network complexity. Experimental results show that our LightDet achieves 75.5% mAP on PASCAL VOC 2007 at the speed of 250 FPS and 24.0% mAP on MS COCO dataset.

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Introduction to the application of service-based blockchain technology in internet of things application

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AIP Conference Proceedings 2024年第1期2895卷

作者： Mohammed L. Khalaf Israa M. Hayder Taief Alaa Al-Amiedy Hussain A. Younis Sani Salisu Ghazwan Abdulnabi Al-Ali Ahmed T. Sadiq Ahmad Sufril Azlan Mohamed School of Computer Sciences Universiti Sains Malaysia 11800 Penang Malaysia Dept. of Computer Systems Techniques Qurna Technique Institute STU 61016 Basrah Iraq National Advanced IPv6 (Nav6) Centre 11800 USM Penang Malaysia College of Education for Women University of Basrah 61004 Basrah Iraq Department of Information Technology Federal University Dutse Jigawa state Dutse Nigeria Department of Computer Science (Educational Science) University of Basrah 61004 Basrah Iraq Computer science department University of Technology 10069 Baghdad Iraq

The Internet of Thing (IoT) is an innovative technology designed to integrate tangible artefacts with the digital era, resulting in the development of new digital services to improve and ease our lives. Despite the advantages of IoT technology in a variety of industries. The existing centralised IoT architecture has a number of issues, including single point of failure, stability, safety, accountability, and data integrity. Such issues are impeding the growth of IoT in the future. To address the a forementioned issues, distributed ledger technologies are regarded as promising and feasible solutions. The blockchain is one of the most prevalent and widely used forms of distributed ledger technology. The combination of IoT and blockchain technology has numerous advantages. The combination of IoT and blockchain technologies will provide numerous benefits. This article demonstrates the fundamentals of IoT and blockchain technology in order to provide a thorough analysis of the architecture of the combination of IoT and blockchain technology. In addition, this study provided a comprehensive description of the combination of the blockchain with the IoT platform from a variety of perspectives in order to address IoT's shortcoming. The service function of blockchain in IoT applications is demonstrated. Finally, the prospective applications of blockchain technology to IoT fields are discussed.

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Iterative Artificial Hummingbird Algorithm-Driven Reconfiguration for microgrids under Multiple Interconnection Scenarios

Energy 360

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Energy 360 2025年 3卷

作者： Ahmed M. Helmi Wiam Ayrir Haitham S. Ramadan Computer Engineering Department College of Engineering and Information Technology Buraydah Private Colleges Buraydah 51418 Saudi Arabia Computer and Systems Engineering Department Faculty of Engineering Zagazig University Zagazig Egypt Advanced Systems Engineering (ASE) Laboratory National School of Applied Sciences Ibn Tofail University Kenitra Morocco Electrical Power and Machines Department Zagazig University Zagazig Egypt Institut International sur le Stockage de l’Hydrogene (ISTHY) Belfort Territory Morvillars 90400 Belfort France

This paper presents a comprehensive study on the reconfiguration of power distribution networks (PDN) within interconnected microgrids (MGs), utilizing the Artificial Hummingbird Algorithm (AHA), Particle Swarm Optimization (PSO), and the Slime Mould Algorithm (SMA) for optimization. The objective is to minimize power loss and improve voltage profiles across the interconnected systems while maintaining a radial topology within each microgrid and the overall interconnection. Building on previous work, which focused solely on horizontal interconnection in two 20-bus systems, this study expands the scope by incorporating vertical and diagonal interconnection scenarios for the 20-bus systems. Additionally, it explores these configurations within a 69-bus system model. Simulation results demonstrate that while all three algorithms improve power loss reduction and voltage stability, AHA consistently outperforms PSO and SMA. The findings contribute to a robust framework for PDN reconfiguration, addressing the complexities of various interconnection configurations and providing valuable insights into enhancing the performance and sustainability of interconnected MGs.

关键词： Power distribution network Reconfiguration Interconnected MGs AHA Optimization Interconnection scenarios

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