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Quantum computing-enhanced topology optimization with stress constraints for truss structures 认领 引用
1
作者 Yan Wang Dixiong Yang +1 位作者 Zhenzeng Lei Guohai Chen 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第6期41-57,共17页
Quantum computing,leveraging the properties of quantum physics such as quantum superposition and entanglement,possesses the potential for exponential acceleration compared to classical computing.It can significantly e... Quantum computing,leveraging the properties of quantum physics such as quantum superposition and entanglement,possesses the potential for exponential acceleration compared to classical computing.It can significantly enhance solution efficiency in topology optimization and effectively avoid the entrapment in local optima.This paper proposes a hybrid classical-quantum computing framework to solve the stress-constrained topology optimization problem for truss structures.Initially,structural analyses are performed on a classical computer to determine the stresses of truss members.Then,the optimization problem is formulated through incremental updates of member cross-sectional areas to make it compatible with a quantum annealer.The update strategy consists of a directional-control function and a magnitude-control function.By embedding stress constraints directly into the directional-control function,the original optimization problem is reformulated as a quadratic unconstrained binary optimization model suitable for quantum annealing.To realize a balance between solution accuracy and iteration efficiency,a dynamic strategy for adjusting the magnitude of area increments is proposed.Thus,the quantum annealer can effectively achieve the optimal solutions.When only the access time of the quantum processing unit is considered,the results from 2D and 3D examples of truss topology optimization validate the effectiveness of the proposed framework,and demonstrate the great potential of quantum computing in structural optimization. 展开更多
关键词 Topology optimization Truss structures Quantum computing Quantum annealing algorithm Quadratic unconstrained binary optimization problem
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Virtual QPU:A Novel Implementation of Quantum Computing 认领 引用
2
作者 Danyang Zheng Jinchen Xv +1 位作者 Xin Zhou Zheng Shan 《Computers, Materials & Continua》 SCIE EI 2026年第4期1008-1029,共22页
The increasing popularity of quantum computing has resulted in a considerable rise in demand for cloud quantum computing usage in recent years.Nevertheless,the rapid surge in demand for cloud-based quantum computing r... The increasing popularity of quantum computing has resulted in a considerable rise in demand for cloud quantum computing usage in recent years.Nevertheless,the rapid surge in demand for cloud-based quantum computing resources has led to a scarcity.In order to meet the needs of an increasing number of researchers,it is imperative to facilitate efficient and flexible access to computing resources in a cloud environment.In this paper,we propose a novel quantum computing paradigm,Virtual QPU(VQPU),which addresses this issue and enhances quantum cloud throughput with guaranteed circuit fidelity.The proposal introduces three innovative concepts:(1)The integration of virtualization technology into the field of quantum computing to enhance quantum cloud throughput.(2)The introduction of an asynchronous execution of circuits methodology to improve quantum computing flexibility.(3)The development of a virtual QPU allocation scheme for quantum tasks in a cloud environment to improve circuit fidelity.The concepts have been validated through the utilization of a self-built simulated quantum cloud platform. 展开更多
关键词 Quantum computing scheduling parallel computing computational paradigm
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Hierarchical QAOA circuit design framework for distributed quantum computing 认领 引用
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作者 Ting-Yu Luo Yu-Xin Deng 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第4期311-327,共17页
The quantum approximate optimization algorithm(QAOA)is a promising approach for solving combinatorial optimization problems on real quantum devices.As QAOA scales to tackle larger problem instances,the limited qubit c... The quantum approximate optimization algorithm(QAOA)is a promising approach for solving combinatorial optimization problems on real quantum devices.As QAOA scales to tackle larger problem instances,the limited qubit capacity of single-chip systems becomes a critical bottleneck.To overcome this limitation,distributed quantum computing(DQC)provides a scalable solution.However,when QAOA circuits are executed in such systems,their performance is significantly hindered by the high cost of remote communication.Motivated by this challenge,we propose HiQ-DF,a QAOA circuit design framework tailored for DQC systems.By employing a hierarchical optimization strategy,HiQ-DF enables comprehensive multi-objective optimization during circuit construction.Experimental results on QAOA circuits solving MaxCut instances show that our framework significantly outperforms baseline methods,achieving an average reduction of 26.12% in EPR pair usage(up to 36.85%),26.44% in circuit latency(up to 35.27%),and 39.63% in circuit depth(up to49.3%). 展开更多
关键词 quantum circuit design quantum approximate optimization algorithm distributed quantum computing
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The Quantum Race China and the U.S.are racing to gain an edge in the next technological frontier,where quantum computing is the engine 认领 引用
4
作者 Wang Yan 《China Report ASEAN》 2026年第5期30-33,共4页
This year's Government Work Report,released during the“two sessions”in March,outlined China's priority tasks for 2026 including“cultivating emerging and future industries.”In this blueprint,“quantum techn... This year's Government Work Report,released during the“two sessions”in March,outlined China's priority tasks for 2026 including“cultivating emerging and future industries.”In this blueprint,“quantum technology”was identified as a future industry. 展开更多
关键词 quantum technology quantum computing future industry emerging future industries China emerging industries U S
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Optical Chips for Quantum Computing and Networking 认领 引用
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《Bulletin of the Chinese Academy of Sciences》 2026年第2期125-127,共3页
The 2026 Tan Kah Kee Young Scientist Award in Information Technical Sciences recognizes the breakthrough work on integrated optical quantum chips led by Professor WANG Jianwei and Professor GONG Qihuang at Peking Univ... The 2026 Tan Kah Kee Young Scientist Award in Information Technical Sciences recognizes the breakthrough work on integrated optical quantum chips led by Professor WANG Jianwei and Professor GONG Qihuang at Peking University.Their team has built chips that combine quantum light sources,optical circuits,and light detectors all on a millimeter-scale chip.This makes it possible to generate,control,and measure quantum states entirely on a single chip,providing a hardware platform that can be scaled up for quantum computing and networking. 展开更多
关键词 light detectors networking integrated optical quantum chips quantum light sourcesoptical circuitsand professor wang jianwei hardware platform quantum computing optical chips
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Scaled Up Chip Pushes Quantum Computing a Bit Closer to Reality 认领 引用 被引量：1
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作者 Chris Palmer 《Engineering》 SCIE EI CSCD 2025年第7期6-8,共3页
In the 9 December 2024 issue of Nature[1],a team of Google engineers reported breakthrough results using“Willow”,their lat-est quantum computing chip(Fig.1).By meeting a milestone“below threshold”reduction in the ... In the 9 December 2024 issue of Nature[1],a team of Google engineers reported breakthrough results using“Willow”,their lat-est quantum computing chip(Fig.1).By meeting a milestone“below threshold”reduction in the rate of errors that plague super-conducting circuit-based quantum computing systems(Fig.2),the work moves the field another step towards its promised super-charged applications,albeit likely still many years away.Areas expected to benefit from quantum computing include,among others,drug discovery,materials science,finance,cybersecurity,and machine learning. 展开更多
关键词 materials science breakthrough drug discovery willow chip quantum computing superconducting circuits error reduction applications
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Developing a Predictive Platform for Salmonella Antimicrobial Resistance Based on a Large Language Model and Quantum Computing 认领 引用
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作者 Yujie You Kan Tan +1 位作者 Zekun Jiang Le Zhang 《Engineering》 SCIE EI CSCD 2025年第5期174-184,共11页
As a common foodborne pathogen,Salmonella poses risks to public health safety,common given the emergence of antimicrobial-resistant strains.However,there is currently a lack of systematic platforms based on large lang... As a common foodborne pathogen,Salmonella poses risks to public health safety,common given the emergence of antimicrobial-resistant strains.However,there is currently a lack of systematic platforms based on large language models(LLMs)for Salmonella resistance prediction,data presentation,and data sharing.To overcome this issue,we firstly propose a two-step feature-selection process based on the chi-square test and conditional mutual information maximization to find the key Salmonella resistance genes in a pan-genomics analysis and develop an LLM-based Salmonella antimicrobial-resistance predictive(SARPLLM)algorithm to achieve accurate antimicrobial-resistance prediction,based on Qwen2 LLM and low-rank adaptation.Secondly,we optimize the time complexity to compute the sample distance from the linear to logarithmic level by constructing a quantum data augmentation algorithm denoted as QSMOTEN.Thirdly,we build up a user-friendly Salmonella antimicrobial-resistance predictive online platform based on knowledge graphs,which not only facilitates online resistance prediction for users but also visualizes the pan-genomics analysis results of the Salmonella datasets. 展开更多
关键词 Salmonella resistance prediction Pan-genomics Large language model Quantum computing Bioinformatics
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Decarbonization of Building Operations with Adaptive Quantum Computing-Based Model Predictive Control 认领 引用
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作者 Akshay Ajagekar Fengqi You 《Engineering》 SCIE EI CSCD 2025年第10期90-103,共14页
This work proposes an adaptive quantum approximate optimization-based model predictive control(MPC)strategy for energy management in buildings equipped with battery energy storage and renewable energy generation syste... This work proposes an adaptive quantum approximate optimization-based model predictive control(MPC)strategy for energy management in buildings equipped with battery energy storage and renewable energy generation systems.The learning-based parameter transfer scheme to realize adaptive quantum optimization leverages Bayesian optimization to predict initial quantum circuit parameters.When applied to the MPC problems formulated as quadratic unconstrained binary optimization problems,this approach computes optimal controls to minimize the net energy consumption levels in buildings and promotes decarbonization while reducing the computational efforts required for the quantum approximate optimization algorithm as the building energy system trajectory progresses.The energy efficiency and the decarbonization benefits of the proposed quantum optimization-based MPC strategy are demonstrated on buildings at the Cornell University campus.The proposed quantum computing-based technique to address MPC problems in buildings demonstrates energy-efficient and low-carbon building operation with a 6.8% improvement over deterministic MPC and presents opportunities for scaling to larger control problems with a significant reduction in utilized quantum computing resources.A reduction of 41.2% in carbon emissions is also achieved with the proposed control strategy facilitated by efficiently managing battery energy storage and renewable generation sources to promote a push toward carbonneutral building operations. 展开更多
关键词 Quantum computing Carbon neutrality Building energy control Quantum approximate optimization
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Quantum Computing Gamble Bets on Stealthy Majorana Qubits 认领 引用
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作者 Chris Palmer 《Engineering》 SCIE EI CSCD 2025年第12期8-10,共3页
With a paper published in the 19 February 2025 issue of Nature[1],Microsoft(Redmond,WA,USA)fanned the flames of its unique vision for quantum computing:a stable,error-resistant qubit based on the Majorana fermion,one ... With a paper published in the 19 February 2025 issue of Nature[1],Microsoft(Redmond,WA,USA)fanned the flames of its unique vision for quantum computing:a stable,error-resistant qubit based on the Majorana fermion,one of the strangest and most elusive particles in physics.The Microsoft Azure Quantum research team’s descriptions of a means to detect the as-yet theoretical particles[1]—called“an entirely new state of matter”by Microsoft’s chief executive officer[2]—and a design for a chip powered by them(Fig.1)[3]have refocused attention on the company’s ambition to build a topological quantum computer.The approach—if it works—could potentially leapfrog every other in the field. 展开更多
关键词 stealthy qubits topological quantum computer majorana fermions stable qubits majorana fermionone error resistant qubits quantum computing microsoft azure
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From portfolio optimization to quantum blockchain and security: a systematic review of quantum computing in finance 认领 引用
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作者 Abha Satyavan Naik Esra Yeniaras +2 位作者 Gerhard Hellstern Grishma Prasad Sanjay Kumar Lalta Prasad Vishwakarma 《Financial Innovation》 2025年第1期2536-2602,共67页
The rapid advancement of quantum computing has sparked a considerable increase in research attention to quantum technologies.These advances span fundamental theoretical inquiries into quantum information and the explo... The rapid advancement of quantum computing has sparked a considerable increase in research attention to quantum technologies.These advances span fundamental theoretical inquiries into quantum information and the exploration of diverse applications arising from this evolving quantum computing paradigm.The scope of the related research is notably diverse.This paper consolidates and presents quantum computing research related to the financial sector.The finance applications considered in this study include portfolio optimization,fraud detection,and Monte Carlo methods for derivative pricing and risk calculation.In addition,we provide a comprehensive analysis of quantum computing’s applications and effects on blockchain technologies,particularly in relation to cryptocurrencies,which are central to financial technology research.As discussed in this study,quantum computing applications in finance are based on fundamental quantum physics principles and key quantum algorithms.This review aims to bridge the research gap between quantum computing and finance.We adopt a two-fold methodology,involving an analysis of quantum algorithms,followed by a discussion of their applications in specific financial contexts.Our study is based on an extensive review of online academic databases,search tools,online journal repositories,and whitepapers from 1952 to 2023,including CiteSeerX,DBLP,Research-Gate,Semantic Scholar,and scientific conference publications.We present state-of-theart findings at the intersection of finance and quantum technology and highlight open research questions that will be valuable for industry practitioners and academicians as they shape future research agendas. 展开更多
关键词 Portfolio optimization Fraud detection Derivative pricing Risk calculation Monte carlo Quantum blockchain Quantum-resistant blockchain Digital signature algorithms Post-quantum cryptography Security Privacy-preserving blockchain Quantum computing
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Privacy-preserving computation meets quantum computing:A scoping review 认领 引用
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作者 Aitor Gómez-Goiri Iñaki Seco-Aguirre +1 位作者 Oscar Lage Alejandra Ruiz 《Digital Communications and Networks》 SCIE EI CSCD 2025年第6期1707-1721,共15页
Privacy-Preserving Computation(PPC)comprises the techniques,schemes and protocols which ensure privacy and confidentiality in the context of secure computation and data analysis.Most of the current PPC techniques rely... Privacy-Preserving Computation(PPC)comprises the techniques,schemes and protocols which ensure privacy and confidentiality in the context of secure computation and data analysis.Most of the current PPC techniques rely on the complexity of cryptographic operations,which are expected to be efficiently solved by quantum computers soon.This review explores how PPC can be built on top of quantum computing itself to alleviate these future threats.We analyze quantum proposals for Secure Multi-party Computation,Oblivious Transfer and Homomorphic Encryption from the last decade focusing on their maturity and the challenges they currently face.Our findings show a strong focus on purely theoretical works,but a rise on the experimental consideration of these techniques in the last 5 years.The applicability of these techniques to actual use cases is an underexplored aspect which could lead to the practical assessment of these techniques. 展开更多
关键词 Quantum computing Privacy-preserving computation Oblivious transfer Secure multi-party computation Homomorphic encryption Scoping review
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Cavity-assisted quantum computing in a silicon nanostructure 认领 引用 被引量：4
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作者 唐宝 秦豪 +2 位作者 张融 刘金明 薛鹏 《Chinese Physics B》 SCIE EI CAS CSCD 2014年第5期86-90,共5页
We present a scheme of quantum computing with charge qubits corresponding to one excess electron shared between dangling-bond pairs of surface silicon atoms that couple to a microwave stripline resonator on a chip. By... We present a scheme of quantum computing with charge qubits corresponding to one excess electron shared between dangling-bond pairs of surface silicon atoms that couple to a microwave stripline resonator on a chip. By choosing a certain evolution time, we propose the realization of a set of universal single-and two-qubit logical gates. Due to its intrinsic stability and scalability, the silicon dangling-bond charge qubit can be regarded as one of the most promising candidates for quantum computation. Compared to the previous schemes on quantum computing with silicon bulk systems, our scheme shows such advantages as a long coherent time and direct control and readout. 展开更多
关键词 quantum computing dangling-bond state
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Quantum computing in power systems 认领 引用 被引量：8
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作者 Yifan Zhou Zefan Tang +5 位作者 Nima Nikmehr Pouya Babahajiani Fei Feng Tzu-Chieh Wei Honghao Zheng Peng Zhang 《iEnergy》 2022年第2期170-187,共18页
Electric power systems provide the backbone of modern industrial societies.Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems.However,today’s power ... Electric power systems provide the backbone of modern industrial societies.Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems.However,today’s power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources,as well as managing huge volumes of data accordingly.These unprecedented challenges call for transformative analytics to support the resilient operations of power systems.Recently,the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations.Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems,which may lead to ultra-scalable and efficient power grid analytics.This paper reviews the newly emerging application of quantum computing techniques in power systems.We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives,including static analysis,transient analysis,stochastic analysis,optimization,stability,and control.We thoroughly discuss the related quantum algorithms,their benefits and limitations,hardware implementations,and recommended practices.We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era.Finally,we discuss challenges and future research directions.This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids. 展开更多
关键词 Quantum computing power system variational quantum algorithms quantum optimization quantum machine learning quantum security
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Selected topics of quantum computing for nuclear physics 认领 引用 被引量：1
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作者 Dan-Bo Zhang Hongxi Xing +2 位作者 Hui Yan Enke Wang Shi-Liang Zhu 《Chinese Physics B》 SCIE EI CAS CSCD 2021年第2期23-34,共12页
Nuclear physics,whose underling theory is described by quantum gauge field coupled with matter,is fundamentally important and yet is formidably challenge for simulation with classical computers.Quantum computing provi... Nuclear physics,whose underling theory is described by quantum gauge field coupled with matter,is fundamentally important and yet is formidably challenge for simulation with classical computers.Quantum computing provides a perhaps transformative approach for studying and understanding nuclear physics.With rapid scaling-up of quantum processors as well as advances on quantum algorithms,the digital quantum simulation approach for simulating quantum gauge fields and nuclear physics has gained lots of attention.In this review,we aim to summarize recent efforts on solving nuclear physics with quantum computers.We first discuss a formulation of nuclear physics in the language of quantum computing.In particular,we review how quantum gauge fields(both Abelian and non-Abelian)and their coupling to matter field can be mapped and studied on a quantum computer.We then introduce related quantum algorithms for solving static properties and real-time evolution for quantum systems,and show their applications for a broad range of problems in nuclear physics,including simulation of lattice gauge field,solving nucleon and nuclear structures,quantum advantage for simulating scattering in quantum field theory,non-equilibrium dynamics,and so on.Finally,a short outlook on future work is given. 展开更多
关键词 quantum computing nuclear physics quantum field theory quantum simulation quantum algorithm
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Quantum Mechanical Nature in Liquid NMR Quantum Computing 认领 引用 被引量：1
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作者 LONGGui－Lu YANHai－Yang 《Communications in Theoretical Physics》 SCIE CAS 2002年第3期305-308,共4页
The quantum nature of bulk ensemble NMR quantum computing — the center of recent heated debate, is addressed. Concepts of the mixed state and entanglement are examined, and the data in a two-qubit liquid NMR quantum ... The quantum nature of bulk ensemble NMR quantum computing — the center of recent heated debate, is addressed. Concepts of the mixed state and entanglement are examined, and the data in a two-qubit liquid NMR quantum computation are analyzed. The main points in this paper are: i) Density matrix describes the 'state' of an average particle in an ensemble. It does not describe the state of an individual particle in an ensemble; ii) Entanglement is a property of the wave function of a microscopic particle (such as a molecule in a liquid NMR sample), and separability of the density matrix cannot be used to measure the entanglement of mixed ensemble; iii) The state evolution in bulk-ensemble NMR quantum computation is quantum-mechanical; iv) The coefficient before the effective pure state density matrix, ?, is a measure of the simultaneity of the molecules in an ensemble. It reflects the intensity of the NMR signal and has no significance in quantifying the entanglement in the bulk ensemble NMR system. The decomposition of the density matrix into product states is only an indication that the ensemble can be prepared by an ensemble with the particles unentangled. We conclude that effective-pure-state NMR quantum computation is genuine, not just classical simulations. 展开更多
关键词 quantum mechanical nature NMR quantum computing mixed state entanglement
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Efficient Scheme for One-Way Quantum Computing with Radiofrequency SQUID Qubits by Adiabatic Passage 认领 引用
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作者 宋明玉 《Communications in Theoretical Physics》 SCIE CAS CSCD 2011年第11期837-844,共8页
We proposed an efficient scheme for constructing a quantum controlled phase-shift gate and generating thecluster states with rf superconducting quantum interference devices (SQUIDs)coupled to a microwave cavity throug... We proposed an efficient scheme for constructing a quantum controlled phase-shift gate and generating thecluster states with rf superconducting quantum interference devices (SQUIDs)coupled to a microwave cavity throughadiabatic evolution of dark eigenstates.During the operation,the spontaneous emission is suppressed since the rf SQUIDsare always in the three lowest flux states.Considering the influence from the cavity decay with achievable experimentalparameters,we numerically analyze the success probability and the fidelity for generating the two-SQUID maximallyentangled state and the controlled phase-shift gate by adiabatic passage. 展开更多
关键词 cluster states quantum computing adiabatic passage
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A Novel Scheduling Framework for Multi-Programming Quantum Computing in Cloud Environment 认领 引用
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作者 Danyang Zheng Jinchen Xv +3 位作者 Feng Yue Qiming Du ZhihengWang Zheng Shan 《Computers, Materials & Continua》 SCIE EI 2024年第5期1957-1974,共18页
As cloud quantum computing gains broader acceptance,a growing quantity of researchers are directing their focus towards this domain.Nevertheless,the rapid surge in demand for cloud-based quantum computing resources ha... As cloud quantum computing gains broader acceptance,a growing quantity of researchers are directing their focus towards this domain.Nevertheless,the rapid surge in demand for cloud-based quantum computing resources has led to a scarcity,which in turn hampers users from achieving optimal satisfaction.Therefore,cloud quantum computing service providers require a unified analysis and scheduling framework for their quantumresources and user jobs to meet the ever-growing usage demands.This paper introduces a new multi-programming scheduling framework for quantum computing in a cloud environment.The framework addresses the issue of limited quantum computing resources in cloud environments and ensures a satisfactory user experience.It introduces three innovative designs:1)Our framework automatically allocates tasks to different quantum backends while ensuring fairness among users by considering both the cloud-based quantum resources and the user-submitted tasks.2)Multi-programming mechanism is employed across different quantum backends to enhance the overall throughput of the quantum cloud.In comparison to conventional task schedulers,our proposed framework achieves a throughput improvement of more than two-fold in the quantum cloud.3)The framework can balance fidelity and user waiting time by adaptively adjusting scheduling parameters. 展开更多
关键词 Quantum computing scheduling multi-programming qubit mapping
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Delayed-measurement one-way quantum computing on cloud quantum computer 认领 引用
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作者 Zhi-Peng Yang Yu-Ran Zhang +1 位作者 Fu-Li Li Heng Fan 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第9期125-131,共7页
One-way quantum computation focuses on initially generating an entangled cluster state followed by a sequence of measurements with classical communication of their individual outcomes.Recently,a delayed-measurement ap... One-way quantum computation focuses on initially generating an entangled cluster state followed by a sequence of measurements with classical communication of their individual outcomes.Recently,a delayed-measurement approach has been applied to replace classical communication of individual measurement outcomes.In this work,by considering the delayed-measurement approach,we demonstrate a modified one-way CNOT gate using the on-cloud superconducting quantum computing platform:Quafu.The modified protocol for one-way quantum computing requires only three qubits rather than the four used in the standard protocol.Since this modified cluster state decreases the number of physical qubits required to implement one-way computation,both the scalability and complexity of the computing process are improved.Compared to previous work,this modified one-way CNOT gate is superior to the standard one in both fidelity and resource requirements.We have also numerically compared the behavior of standard and modified methods in large-scale one-way quantum computing.Our results suggest that in a noisy intermediate-scale quantum(NISQ)era,the modified method shows a significant advantage for one-way quantum computation. 展开更多
关键词 measurement-based quantum computing quantum entanglement quantum gates
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Automatic architecture design for distributed quantum computing 认领 引用
19
作者 Ting-Yu Luo Yu-Zhen Zheng +1 位作者 Xiang Fu Yu-Xin Deng 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第12期45-59,共15页
In distributed quantum computing(DQC),quantum hardware design mainly focuses on providing as many as possible high-quality inter-chip connections.Meanwhile,quantum software tries its best to reduce the required number... In distributed quantum computing(DQC),quantum hardware design mainly focuses on providing as many as possible high-quality inter-chip connections.Meanwhile,quantum software tries its best to reduce the required number of remote quantum gates between chips.However,this“hardware first,software follows”methodology may not fully exploit the potential of DQC.Inspired by classical software-hardware co-design,this paper explores the design space of application-specific DQC architectures.More specifically,we propose Auto Arch,an automated quantum chip network(QCN)structure design tool.With qubits grouping followed by a customized QCN design,AutoArch can generate a near-optimal DQC architecture suitable for target quantum algorithms.Experimental results show that the DQC architecture generated by Auto Arch can outperform other general QCN architectures when executing target quantum algorithms. 展开更多
关键词 distributed quantum computing quantum architecture quantum circuit partitioning
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Quantum Computing Based Neural Networks for Anomaly Classification in Real-Time Surveillance Videos 认领 引用
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作者 MD.Yasar Arafath A.Niranjil Kumar 《Computer Systems Science & Engineering》 SCIE EI 2023年第8期2489-2508,共20页
For intelligent surveillance videos,anomaly detection is extremely important.Deep learning algorithms have been popular for evaluating realtime surveillance recordings,like traffic accidents,and criminal or unlawful i... For intelligent surveillance videos,anomaly detection is extremely important.Deep learning algorithms have been popular for evaluating realtime surveillance recordings,like traffic accidents,and criminal or unlawful incidents such as suicide attempts.Nevertheless,Deep learning methods for classification,like convolutional neural networks,necessitate a lot of computing power.Quantum computing is a branch of technology that solves abnormal and complex problems using quantum mechanics.As a result,the focus of this research is on developing a hybrid quantum computing model which is based on deep learning.This research develops a Quantum Computing-based Convolutional Neural Network(QC-CNN)to extract features and classify anomalies from surveillance footage.A Quantum-based Circuit,such as the real amplitude circuit,is utilized to improve the performance of the model.As far as my research,this is the first work to employ quantum deep learning techniques to classify anomalous events in video surveillance applications.There are 13 anomalies classified from the UCF-crime dataset.Based on experimental results,the proposed model is capable of efficiently classifying data concerning confusion matrix,Receiver Operating Characteristic(ROC),accuracy,Area Under Curve(AUC),precision,recall as well as F1-score.The proposed QC-CNN has attained the best accuracy of 95.65 percent which is 5.37%greater when compared to other existing models.To measure the efficiency of the proposed work,QC-CNN is also evaluated with classical and quantum models. 展开更多
关键词 Deep learning video surveillance quantum computing anomaly detection convolutional neural network
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