Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing o...Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing offers a transformative approach to solve ADN planning.To fully leverage the potential of quantum computing,this paper proposes a photonic quantum acceleration algorithm.First,a quantum-accelerated framework for ADN planning is proposed on the basis of coherent photonic quantum computers.The ADN planning model is then formulated and decomposed into discrete master problems and continuous subproblems to facilitate the quantum optimization process.The photonic quantum-embedded adaptive alternating direction method of multipliers(PQA-ADMM)algorithm is subsequently proposed to equivalently map the discrete master problem onto a quantum-interpretable model,enabling its deployment on a photonic quantum computer.Finally,a comparative analysis with various solvers,including Gurobi,demonstrates that the proposed PQA-ADMM algorithm achieves significant speedup on the modified IEEE 33-node and IEEE 123-node systems,highlighting its effectiveness.展开更多
Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousa...Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousands of alarmed tech leaders recently signed an open letter to pause AI research to prepare for the catastrophic threats to humanity from uncontrolled AGI (Artificial General Intelligence). Perceived as an “epistemological nightmare”, AGI is believed to be on the anvil with GPT-5. Two computing rules appear responsible for these risks. 1) Mandatory third-party permissions that allow computers to run applications at the expense of introducing vulnerabilities. 2) The Halting Problem of Turing-complete AI programming languages potentially renders AGI unstoppable. The double whammy of these inherent weaknesses remains invincible under the legacy systems. A recent cybersecurity breakthrough shows that banning all permissions reduces the computer attack surface to zero, delivering a new zero vulnerability computing (ZVC) paradigm. Deploying ZVC and blockchain, this paper formulates and supports a hypothesis: “Safe, secure, ethical, controllable AGI/QC is possible by conquering the two unassailable rules of computability.” Pursued by a European consortium, testing/proving the proposed hypothesis will have a groundbreaking impact on the future digital infrastructure when AGI/QC starts powering the 75 billion internet devices by 2025.展开更多
In the effort to develop useful quantum computers,simulating quantum machines with conventional classical computing resources is a key capability.Such simulations will always face limits,preventing the emulation of qu...In the effort to develop useful quantum computers,simulating quantum machines with conventional classical computing resources is a key capability.Such simulations will always face limits,preventing the emulation of quantum computers at substantial scale;however,by pushing the envelope through optimal choices of algorithms and hardware,the value of simulator tools can be maximized.This work reviews state-of-the-art numerical simulation methods,i.e.,classical algorithms that emulate quantum computer evolution under specific operations.We focus on the mainstream state-vector and tensor-network paradigms,while briefly mentioning alternative methods.Moreover,we review the diverse applications of simulation across different facets of quantum computer development,including understanding the fundamental differences between quantum and classical computations,exploring algorithmic design for quantum advantage,predicting quantum processor performance at the design stage,and efficiently characterizing fabricated devices for rapid iterations.This review complements recent surveys of current tools and implementations;here,we aim to provide readers with an essential understanding of the theoretical basis of classical simulation methods,a detailed discussion of their advantages and limitations,and an overview of the demands and challenges arising from practical use cases.展开更多
Nonadiabatic holonomic quantum computers serve as the physical platform for nonadiabatic holonomic quantum computation.As quantum computation has entered the noisy intermediate-scale era,building accurate intermediate...Nonadiabatic holonomic quantum computers serve as the physical platform for nonadiabatic holonomic quantum computation.As quantum computation has entered the noisy intermediate-scale era,building accurate intermediate-scale nonadiabatic holo-nomic quantum computers is clearly necessary.Given that measurements are the sole means of extracting information,they play an indispensable role in nonadiabatic holonomic quantum computers.Accordingly,developing methods to reduce measurement errors in nonadiabatic holonomic quantum computers is of great importance.However,while much attention has been given to the research on nonadiabatic holonomic gates,the research on reducing measurement errors in nonadiabatic holonomic quantum computers is severely lacking.In this study,we propose a measurement error reduction method tailored for intermediate-scale nonadiabatic holonomic quantum computers.The reason we say this is because our method can not only reduce the measurement errors in the computer but also be useful in mitigating errors originating from nonadiabatic holonomic gates.Given these features,our method significantly advances the construction of accurate intermediate-scale nonadiabatic holonomic quantum computers.展开更多
Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and v...Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and viable quantum algorithms for simulating large-scale materials are still limited.We propose and implement random-state quantum algorithms to calculate electronic-structure properties of real materials.Using a random state circuit on a small number of qubits,we employ real-time evolution with first-order Trotter decomposition and Hadamard test to obtain electronic density of states,and we develop a modified quantum phase estimation algorithm to calculate real-space local density of states via direct quantum measurements.Furthermore,we validate these algorithms by numerically computing the density of states and spatial distributions of electronic states in graphene,twisted bilayer graphene quasicrystals,and fractal lattices,covering system sizes from hundreds to thousands of atoms.Our results manifest that the random-state quantum algorithms provide a general and qubit-efficient route to scalable simulations of electronic properties in large-scale periodic and aperiodic materials.展开更多
As an important index to measure the degree of entanglement in quantum systems,concurrence plays an important role in practical research.In this paper,we study the concurrence between two qubits in triangular triple q...As an important index to measure the degree of entanglement in quantum systems,concurrence plays an important role in practical research.In this paper,we study the concurrence between two qubits in triangular triple quantum dot structure.Through calculation and simulation,it is found that concurrence is mainly affected by the interdot coupling strength t,Coulomb interactionU,temperature T,and electrode coupling G.Through comparative studies with parallel triple quantum dot structures,we demonstrate that the triangular geometry exhibits significantly enhanced concurrence under identical conditions.In addition,under the condition that concurrence exceeds 0.9,the functional relationship between t and U is obtained through simulation,which provides theoretical support for quantum dot regulation under high entanglement.Finally,we demonstrate the feasibility of implementing a three-qubit quantum gate,using the Toffoli gate as a representative example,under the condition that the triangular triple quantum dot system maintains high entanglement.展开更多
The advent of quantum computing poses a significant challenge to traditional cryptographic protocols,particularly those used in SecureMultiparty Computation(MPC),a fundamental cryptographic primitive for privacypreser...The advent of quantum computing poses a significant challenge to traditional cryptographic protocols,particularly those used in SecureMultiparty Computation(MPC),a fundamental cryptographic primitive for privacypreserving computation.Classical MPC relies on cryptographic techniques such as homomorphic encryption,secret sharing,and oblivious transfer,which may become vulnerable in the post-quantum era due to the computational power of quantum adversaries.This study presents a review of 140 peer-reviewed articles published between 2000 and 2025 that used different databases like MDPI,IEEE Explore,Springer,and Elsevier,examining the applications,types,and security issues with the solution of Quantum computing in different fields.This review explores the impact of quantum computing on MPC security,assesses emerging quantum-resistant MPC protocols,and examines hybrid classicalquantum approaches aimed at mitigating quantum threats.We analyze the role of Quantum Key Distribution(QKD),post-quantum cryptography(PQC),and quantum homomorphic encryption in securing multiparty computations.Additionally,we discuss the challenges of scalability,computational efficiency,and practical deployment of quantumsecure MPC frameworks in real-world applications such as privacy-preserving AI,secure blockchain transactions,and confidential data analysis.This review provides insights into the future research directions and open challenges in ensuring secure,scalable,and quantum-resistant multiparty computation.展开更多
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
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
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
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
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
A team of researchers from the University of Science and Technology of China(USTC)of the Chinese Academy of Sciences(CAS)and its partners have made significant advancements in random quantum circuit sampling with Zuch...A team of researchers from the University of Science and Technology of China(USTC)of the Chinese Academy of Sciences(CAS)and its partners have made significant advancements in random quantum circuit sampling with Zuchongzhi-3,a superconducting quantum computing prototype featuring 105 qubits and 182 couplers.展开更多
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
Effective resource management in the Internet of Things and fog computing is essential for efficient and scalable networks.However,existing methods often fail in dynamic and high-demand environments,leading to resourc...Effective resource management in the Internet of Things and fog computing is essential for efficient and scalable networks.However,existing methods often fail in dynamic and high-demand environments,leading to resource bottlenecks and increased energy consumption.This study aims to address these limitations by proposing the Quantum Inspired Adaptive Resource Management(QIARM)model,which introduces novel algorithms inspired by quantum principles for enhanced resource allocation.QIARM employs a quantum superposition-inspired technique for multi-state resource representation and an adaptive learning component to adjust resources in real time dynamically.In addition,an energy-aware scheduling module minimizes power consumption by selecting optimal configurations based on energy metrics.The simulation was carried out in a 360-minute environment with eight distinct scenarios.This study introduces a novel quantum-inspired resource management framework that achieves up to 98%task offload success and reduces energy consumption by 20%,addressing critical challenges of scalability and efficiency in dynamic fog computing environments.展开更多
We present a robust quantum optimal control framework for implementing fast entangling gates on ion-trap quantum processors.The framework leverages tailored laser pulses to drive the multiple vibrational sidebands of ...We present a robust quantum optimal control framework for implementing fast entangling gates on ion-trap quantum processors.The framework leverages tailored laser pulses to drive the multiple vibrational sidebands of the ions to create phonon-mediated entangling gates and,unlike the state of the art,requires neither weakcoupling Lamb-Dicke approximation nor perturbation treatment.With the application of gradient-based optimal control,it enables finding amplitude-and phase-modulated laser control protocols that work without the Lamb-Dicke approximation,promising gate speeds on the order of microseconds comparable to the characteristic trap frequencies.Also,robustness requirements on the temperature of the ions and initial optical phase can be conveniently included to pursue high-quality fast gates against experimental imperfections.Our approach represents a step in speeding up quantum gates to achieve larger quantum circuits for quantum computation and simulation,and thus can find applications in near-future experiments.展开更多
This study aims to develop a quantum computing-based neurocognitive architecture that allows an agent to perform autonomous behaviors.Therefore,we present a brain-inspired cognitive architecture for autonomous agents ...This study aims to develop a quantum computing-based neurocognitive architecture that allows an agent to perform autonomous behaviors.Therefore,we present a brain-inspired cognitive architecture for autonomous agents that integrates a prefrontal cortex-inspired model with modern deep learning(a transformer-based reinforcement learning module)and quantum algorithms.In particular,our framework incorporates quantum computational routines(Deutsch-Jozsa,Bernstein-Vazirani,and Grover’s search)to enhance decision-making efficiency.As a novelty of this research,this comprehensive computational structure is empowered by quantum computing operations so that superiority in speed and robustness of learning compared to classical methods can be demonstrated.Another main contribution is that the proposed architecture offers some features,such as meta-cognition and situation awareness.The meta-cognition aspect is responsible for hierarchically learning sub-tasks,enabling the agent to achieve the master goal.The situation-awareness property identifies how spatial-temporal reasoning activities related to the world model of the agent can be extracted in a dynamic simulation environment with unstructured uncertainties by quantum computation-based machine learning algorithms with the explainable artificial intelligence paradigm.In this research,the Minecraft game-based simulation environment is utilized for the experimental evaluation of performance and verification tests within complex,multi-objective tasks related to the autonomous behaviors of a smart agent.By implementing several interaction scenarios,the results of the system performance and comparative superiority over alternative solutions are presented,and it is discussed how these autonomous behaviors and cognitive skills of a smart agent can be improved in further studies.Results show that the quantum-enhanced agent achieves faster convergence to an 80%task 2×success rate in exploration tasks and approximately 15%higher cumulative rewards compared to a classical deep RL baseline.These findings demonstrate the potential of quantum algorithms to significantly improve learning and performance in cognitive agent architectures.However,advantages are task-specific and less pronounced under high-uncertainty,reactive scenarios.Limitations of the simulation environment are acknowledged,and a structured future research roadmap is proposed involving highfidelity simulation validation,hardware-in-the-loop robotic testing,and integration of advanced hybrid quantum-classical architectures.展开更多
In the current noisy intermediate-scale quantum(NISQ)era,a single quantum processing unit(QPU)is insufficient to implement large-scale quantum algorithms;this has driven extensive research into distributed quantum com...In the current noisy intermediate-scale quantum(NISQ)era,a single quantum processing unit(QPU)is insufficient to implement large-scale quantum algorithms;this has driven extensive research into distributed quantum computing(DQC).DQC involves the cooperative operation of multiple QPUs but is concurrently challenged by excessive communication complexity.To address this issue,this paper proposes a quantum circuit partitioning method based on spectral clustering.The approach transforms quantum circuits into weighted graphs and,through computation of the Laplacian matrix and clustering techniques,identifies candidate partition schemes that minimize the total weight of the cut.Additionally,a global gate search tree strategy is introduced to meticulously explore opportunities for merged transfer of global gates,thereby minimizing the transmission cost of distributed quantum circuits and selecting the optimal partition scheme from the candidates.Finally,the proposed method is evaluated through various comparative experiments.The experimental results demonstrate that spectral clustering-based partitioning exhibits robust stability and efficiency in runtime in quantum circuits of different scales.In experiments involving the quantum Fourier transform algorithm and Revlib quantum circuits,the transmission cost achieved by the global gate search tree strategy is significantly optimized.展开更多
Preparing quantum superposition states is a crucial step in realizing quantum algorithms,which demands substantial resources.In this paper,we propose a new method for preparing quantum uniform superposition states via...Preparing quantum superposition states is a crucial step in realizing quantum algorithms,which demands substantial resources.In this paper,we propose a new method for preparing quantum uniform superposition states via quantum measurement,and design the bitwise implementation circuit,which only contains Hadamard,CNOT,and π/8 phase gates.Compared to the Shukla–Vedula method,the number of quantum gates required by both methods scales the same,while,the new method offers stronger fault tolerance,and the ancillary qubits employed during the implementation process can be reused,making it more suitable for implementation on real quantum computers.As an application,we provide the circuit for Shor's discrete logarithm quantum algorithm,based on the new method,demonstrating its technical advantage for implementation of quantum algorithms.展开更多
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
基金supported in part by the National Natural Science Foundation of China under Grant 52307134the Fundamental Research Funds for the Central Universities(xzy012025022)。
文摘Active distribution network(ADN)planning is crucial for achieving a cost-effective transition to modern power systems,yet it poses significant challenges as the system scale increases.The advent of quantum computing offers a transformative approach to solve ADN planning.To fully leverage the potential of quantum computing,this paper proposes a photonic quantum acceleration algorithm.First,a quantum-accelerated framework for ADN planning is proposed on the basis of coherent photonic quantum computers.The ADN planning model is then formulated and decomposed into discrete master problems and continuous subproblems to facilitate the quantum optimization process.The photonic quantum-embedded adaptive alternating direction method of multipliers(PQA-ADMM)algorithm is subsequently proposed to equivalently map the discrete master problem onto a quantum-interpretable model,enabling its deployment on a photonic quantum computer.Finally,a comparative analysis with various solvers,including Gurobi,demonstrates that the proposed PQA-ADMM algorithm achieves significant speedup on the modified IEEE 33-node and IEEE 123-node systems,highlighting its effectiveness.
文摘Although AI and quantum computing (QC) are fast emerging as key enablers of the future Internet, experts believe they pose an existential threat to humanity. Responding to the frenzied release of ChatGPT/GPT-4, thousands of alarmed tech leaders recently signed an open letter to pause AI research to prepare for the catastrophic threats to humanity from uncontrolled AGI (Artificial General Intelligence). Perceived as an “epistemological nightmare”, AGI is believed to be on the anvil with GPT-5. Two computing rules appear responsible for these risks. 1) Mandatory third-party permissions that allow computers to run applications at the expense of introducing vulnerabilities. 2) The Halting Problem of Turing-complete AI programming languages potentially renders AGI unstoppable. The double whammy of these inherent weaknesses remains invincible under the legacy systems. A recent cybersecurity breakthrough shows that banning all permissions reduces the computer attack surface to zero, delivering a new zero vulnerability computing (ZVC) paradigm. Deploying ZVC and blockchain, this paper formulates and supports a hypothesis: “Safe, secure, ethical, controllable AGI/QC is possible by conquering the two unassailable rules of computability.” Pursued by a European consortium, testing/proving the proposed hypothesis will have a groundbreaking impact on the future digital infrastructure when AGI/QC starts powering the 75 billion internet devices by 2025.
基金supported by the National Natural Science Foundation of China(12325501 and 12447101).
文摘In the effort to develop useful quantum computers,simulating quantum machines with conventional classical computing resources is a key capability.Such simulations will always face limits,preventing the emulation of quantum computers at substantial scale;however,by pushing the envelope through optimal choices of algorithms and hardware,the value of simulator tools can be maximized.This work reviews state-of-the-art numerical simulation methods,i.e.,classical algorithms that emulate quantum computer evolution under specific operations.We focus on the mainstream state-vector and tensor-network paradigms,while briefly mentioning alternative methods.Moreover,we review the diverse applications of simulation across different facets of quantum computer development,including understanding the fundamental differences between quantum and classical computations,exploring algorithmic design for quantum advantage,predicting quantum processor performance at the design stage,and efficiently characterizing fabricated devices for rapid iterations.This review complements recent surveys of current tools and implementations;here,we aim to provide readers with an essential understanding of the theoretical basis of classical simulation methods,a detailed discussion of their advantages and limitations,and an overview of the demands and challenges arising from practical use cases.
基金supported by the National Natural Science Foundation of China(Grant No.12174224)。
文摘Nonadiabatic holonomic quantum computers serve as the physical platform for nonadiabatic holonomic quantum computation.As quantum computation has entered the noisy intermediate-scale era,building accurate intermediate-scale nonadiabatic holo-nomic quantum computers is clearly necessary.Given that measurements are the sole means of extracting information,they play an indispensable role in nonadiabatic holonomic quantum computers.Accordingly,developing methods to reduce measurement errors in nonadiabatic holonomic quantum computers is of great importance.However,while much attention has been given to the research on nonadiabatic holonomic gates,the research on reducing measurement errors in nonadiabatic holonomic quantum computers is severely lacking.In this study,we propose a measurement error reduction method tailored for intermediate-scale nonadiabatic holonomic quantum computers.The reason we say this is because our method can not only reduce the measurement errors in the computer but also be useful in mitigating errors originating from nonadiabatic holonomic gates.Given these features,our method significantly advances the construction of accurate intermediate-scale nonadiabatic holonomic quantum computers.
基金supported by the Major Project for the Integration of ScienceEducation and Industry (Grant No.2025ZDZX02)。
文摘Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and viable quantum algorithms for simulating large-scale materials are still limited.We propose and implement random-state quantum algorithms to calculate electronic-structure properties of real materials.Using a random state circuit on a small number of qubits,we employ real-time evolution with first-order Trotter decomposition and Hadamard test to obtain electronic density of states,and we develop a modified quantum phase estimation algorithm to calculate real-space local density of states via direct quantum measurements.Furthermore,we validate these algorithms by numerically computing the density of states and spatial distributions of electronic states in graphene,twisted bilayer graphene quasicrystals,and fractal lattices,covering system sizes from hundreds to thousands of atoms.Our results manifest that the random-state quantum algorithms provide a general and qubit-efficient route to scalable simulations of electronic properties in large-scale periodic and aperiodic materials.
文摘As an important index to measure the degree of entanglement in quantum systems,concurrence plays an important role in practical research.In this paper,we study the concurrence between two qubits in triangular triple quantum dot structure.Through calculation and simulation,it is found that concurrence is mainly affected by the interdot coupling strength t,Coulomb interactionU,temperature T,and electrode coupling G.Through comparative studies with parallel triple quantum dot structures,we demonstrate that the triangular geometry exhibits significantly enhanced concurrence under identical conditions.In addition,under the condition that concurrence exceeds 0.9,the functional relationship between t and U is obtained through simulation,which provides theoretical support for quantum dot regulation under high entanglement.Finally,we demonstrate the feasibility of implementing a three-qubit quantum gate,using the Toffoli gate as a representative example,under the condition that the triangular triple quantum dot system maintains high entanglement.
文摘The advent of quantum computing poses a significant challenge to traditional cryptographic protocols,particularly those used in SecureMultiparty Computation(MPC),a fundamental cryptographic primitive for privacypreserving computation.Classical MPC relies on cryptographic techniques such as homomorphic encryption,secret sharing,and oblivious transfer,which may become vulnerable in the post-quantum era due to the computational power of quantum adversaries.This study presents a review of 140 peer-reviewed articles published between 2000 and 2025 that used different databases like MDPI,IEEE Explore,Springer,and Elsevier,examining the applications,types,and security issues with the solution of Quantum computing in different fields.This review explores the impact of quantum computing on MPC security,assesses emerging quantum-resistant MPC protocols,and examines hybrid classicalquantum approaches aimed at mitigating quantum threats.We analyze the role of Quantum Key Distribution(QKD),post-quantum cryptography(PQC),and quantum homomorphic encryption in securing multiparty computations.Additionally,we discuss the challenges of scalability,computational efficiency,and practical deployment of quantumsecure MPC frameworks in real-world applications such as privacy-preserving AI,secure blockchain transactions,and confidential data analysis.This review provides insights into the future research directions and open challenges in ensuring secure,scalable,and quantum-resistant multiparty computation.
文摘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.
文摘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.
基金Gerhard Hellstern is partly funded by the Ministry of Economic Affairs,Labour and Tourism Baden-Württemberg in the frame of the Competence Center Quantum Computing Baden-Württemberg(QORA Ⅱ).
文摘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.
文摘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.
基金supported by the Basque Government through the ELKARTEK program for Research and Innovation,under the BRTAQUANTUM project(Grant Agreement No.KK-2022/00041)。
文摘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.
文摘A team of researchers from the University of Science and Technology of China(USTC)of the Chinese Academy of Sciences(CAS)and its partners have made significant advancements in random quantum circuit sampling with Zuchongzhi-3,a superconducting quantum computing prototype featuring 105 qubits and 182 couplers.
基金supported by the National Science and Technology Major Project(2021YFF1201200)the National Natural Science Foundation of China(62372316)the Sichuan Science and Technology Program key project(2024YFHZ0091).
文摘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.
基金funded by Researchers Supporting Project Number(RSPD2025R947)King Saud University,Riyadh,Saudi Arabia.
文摘Effective resource management in the Internet of Things and fog computing is essential for efficient and scalable networks.However,existing methods often fail in dynamic and high-demand environments,leading to resource bottlenecks and increased energy consumption.This study aims to address these limitations by proposing the Quantum Inspired Adaptive Resource Management(QIARM)model,which introduces novel algorithms inspired by quantum principles for enhanced resource allocation.QIARM employs a quantum superposition-inspired technique for multi-state resource representation and an adaptive learning component to adjust resources in real time dynamically.In addition,an energy-aware scheduling module minimizes power consumption by selecting optimal configurations based on energy metrics.The simulation was carried out in a 360-minute environment with eight distinct scenarios.This study introduces a novel quantum-inspired resource management framework that achieves up to 98%task offload success and reduces energy consumption by 20%,addressing critical challenges of scalability and efficiency in dynamic fog computing environments.
基金supported by the National Natural Science Foundation of China(Grant Nos.12441502,12122506,12204230,and 12404554)the National Science and Technology Major Project of the Ministry of Science and Technology of China(2024ZD0300404)+6 种基金Guangdong Basic and Applied Basic Research Foundation(Grant No.2021B1515020070)Shenzhen Science and Technology Program(Grant No.RCYX20200714114522109)China Postdoctoral Science Foundation(CPSF)(2024M762114)Postdoctoral Fellowship Program of CPSF(GZC20231727)supported by the National Natural Science Foundation of China(Grant Nos.92165206 and 11974330)Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301603)the Fundamental Research Funds for the Central Universities。
文摘We present a robust quantum optimal control framework for implementing fast entangling gates on ion-trap quantum processors.The framework leverages tailored laser pulses to drive the multiple vibrational sidebands of the ions to create phonon-mediated entangling gates and,unlike the state of the art,requires neither weakcoupling Lamb-Dicke approximation nor perturbation treatment.With the application of gradient-based optimal control,it enables finding amplitude-and phase-modulated laser control protocols that work without the Lamb-Dicke approximation,promising gate speeds on the order of microseconds comparable to the characteristic trap frequencies.Also,robustness requirements on the temperature of the ions and initial optical phase can be conveniently included to pursue high-quality fast gates against experimental imperfections.Our approach represents a step in speeding up quantum gates to achieve larger quantum circuits for quantum computation and simulation,and thus can find applications in near-future experiments.
文摘This study aims to develop a quantum computing-based neurocognitive architecture that allows an agent to perform autonomous behaviors.Therefore,we present a brain-inspired cognitive architecture for autonomous agents that integrates a prefrontal cortex-inspired model with modern deep learning(a transformer-based reinforcement learning module)and quantum algorithms.In particular,our framework incorporates quantum computational routines(Deutsch-Jozsa,Bernstein-Vazirani,and Grover’s search)to enhance decision-making efficiency.As a novelty of this research,this comprehensive computational structure is empowered by quantum computing operations so that superiority in speed and robustness of learning compared to classical methods can be demonstrated.Another main contribution is that the proposed architecture offers some features,such as meta-cognition and situation awareness.The meta-cognition aspect is responsible for hierarchically learning sub-tasks,enabling the agent to achieve the master goal.The situation-awareness property identifies how spatial-temporal reasoning activities related to the world model of the agent can be extracted in a dynamic simulation environment with unstructured uncertainties by quantum computation-based machine learning algorithms with the explainable artificial intelligence paradigm.In this research,the Minecraft game-based simulation environment is utilized for the experimental evaluation of performance and verification tests within complex,multi-objective tasks related to the autonomous behaviors of a smart agent.By implementing several interaction scenarios,the results of the system performance and comparative superiority over alternative solutions are presented,and it is discussed how these autonomous behaviors and cognitive skills of a smart agent can be improved in further studies.Results show that the quantum-enhanced agent achieves faster convergence to an 80%task 2×success rate in exploration tasks and approximately 15%higher cumulative rewards compared to a classical deep RL baseline.These findings demonstrate the potential of quantum algorithms to significantly improve learning and performance in cognitive agent architectures.However,advantages are task-specific and less pronounced under high-uncertainty,reactive scenarios.Limitations of the simulation environment are acknowledged,and a structured future research roadmap is proposed involving highfidelity simulation validation,hardware-in-the-loop robotic testing,and integration of advanced hybrid quantum-classical architectures.
基金supported by the National Natural Science Foundation of China(Grant No.62072259)in part by the Natural Science Foundation of Jiangsu Province(Grant No.BK20221411)+1 种基金the PhD Start-up Fund of Nantong University(Grant No.23B03)the Postgraduate Research&Practice Innovation Program of School of Information Science and Technology,Nantong University(Grant No.NTUSISTPR2405).
文摘In the current noisy intermediate-scale quantum(NISQ)era,a single quantum processing unit(QPU)is insufficient to implement large-scale quantum algorithms;this has driven extensive research into distributed quantum computing(DQC).DQC involves the cooperative operation of multiple QPUs but is concurrently challenged by excessive communication complexity.To address this issue,this paper proposes a quantum circuit partitioning method based on spectral clustering.The approach transforms quantum circuits into weighted graphs and,through computation of the Laplacian matrix and clustering techniques,identifies candidate partition schemes that minimize the total weight of the cut.Additionally,a global gate search tree strategy is introduced to meticulously explore opportunities for merged transfer of global gates,thereby minimizing the transmission cost of distributed quantum circuits and selecting the optimal partition scheme from the candidates.Finally,the proposed method is evaluated through various comparative experiments.The experimental results demonstrate that spectral clustering-based partitioning exhibits robust stability and efficiency in runtime in quantum circuits of different scales.In experiments involving the quantum Fourier transform algorithm and Revlib quantum circuits,the transmission cost achieved by the global gate search tree strategy is significantly optimized.
基金supported by National Key Research and Development Program of China(Grant No.2020YFA0309702)the National Natural Science Foundation of China(Grant No.61502526)+1 种基金NSAF(Grant No.U2130205)the Natural Science Foundation of Henan Province,China(Grant Nos.202300410532 and 252300421818)。
文摘Preparing quantum superposition states is a crucial step in realizing quantum algorithms,which demands substantial resources.In this paper,we propose a new method for preparing quantum uniform superposition states via quantum measurement,and design the bitwise implementation circuit,which only contains Hadamard,CNOT,and π/8 phase gates.Compared to the Shukla–Vedula method,the number of quantum gates required by both methods scales the same,while,the new method offers stronger fault tolerance,and the ancillary qubits employed during the implementation process can be reused,making it more suitable for implementation on real quantum computers.As an application,we provide the circuit for Shor's discrete logarithm quantum algorithm,based on the new method,demonstrating its technical advantage for implementation of quantum algorithms.
文摘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.
