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
As technological innovations in computers begin to advance past their limit (Moore’s law), a new problem arises: What computational device would emerge after the classical supercomputers reach their physical limitati...As technological innovations in computers begin to advance past their limit (Moore’s law), a new problem arises: What computational device would emerge after the classical supercomputers reach their physical limitations? At this moment in time, quantum computers are at their starting stage and there are already some strengths and advantages when compared with modern, classical computers. In its testing period, there are a variety of ways to create a quantum computer by processes such as the trapped-ion and the spin-dot methods. Nowadays, there are many drawbacks with quantum computers such as issues with decoherence and scalability, but many of these issues are easily emended. Nevertheless, the benefits of quantum computers at the moment outweigh the potential drawbacks. These benefits include its use of many properties of quantum mechanics such as quantum superposition, entanglement, and parallelism. Using these basic properties of quantum mechanics, quantum computers are capable of achieving faster computational times for certain problems such as finding prime factors of an integer by using Shor’s algorithm. From the advantages such as faster computing times in certain situations and higher computing powers than classical computers, quantum computers have a high probability to be the future of computing after classical computers hit their peak.展开更多
Quantum singular value thresholding(QSVT) algorithm,as a core module of many mathematical models,seeks the singular values of a sparse and low rank matrix exceeding a threshold and their associated singular vectors.Th...Quantum singular value thresholding(QSVT) algorithm,as a core module of many mathematical models,seeks the singular values of a sparse and low rank matrix exceeding a threshold and their associated singular vectors.The existing all-qubit QSVT algorithm demands lots of ancillary qubits,remaining a huge challenge for realization on nearterm intermediate-scale quantum computers.In this paper,we propose a hybrid QSVT(HQSVT) algorithm utilizing both discrete variables(DVs) and continuous variables(CVs).In our algorithm,raw data vectors are encoded into a qubit system and the following data processing is fulfilled by hybrid quantum operations.Our algorithm requires O [log(MN)] qubits with0(1) qumodes and totally performs 0(1) operations,which significantly reduces the space and runtime consumption.展开更多
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
A theoretical model of computation is proposed based on Lorentz quantum mechanics.Besides the standard qubits,this model has an additional bit,which we call hyperbolic bit(or hybit in short).A set of basic logical gat...A theoretical model of computation is proposed based on Lorentz quantum mechanics.Besides the standard qubits,this model has an additional bit,which we call hyperbolic bit(or hybit in short).A set of basic logical gates are constructed and their universality is proved.As an application,a search algorithm is designed for this computer model and is found to be exponentially faster than Grover's search algorithm.展开更多
This paper investigatesWindfarmLayoutOptimization(WFLO),where we formulate turbine placement considering wake effects as a Quadratic Unconstrained Binary Optimization(QUBO)problem.Wind energy plays a critical role in ...This paper investigatesWindfarmLayoutOptimization(WFLO),where we formulate turbine placement considering wake effects as a Quadratic Unconstrained Binary Optimization(QUBO)problem.Wind energy plays a critical role in the transition toward sustainable power systems,but the optimal placement of turbines remains a challenging combinatorial problem due to complex wake interactions.With recent advances in quantum computing,there is growing interest in exploring whether hybrid quantum-classical methods can provide advantages for such computationally intensive tasks.We investigate solving the resulting QUBO problem using the Variational Quantum Eigensolver(VQE)implemented onQiskit’s quantum computer simulator,employing a quantum noise-free,gate-based circuit model.Three classical optimizers are discussed,with a detailed analysis of the two most effective approaches:Constrained Optimization BY Linear Approximation(COBYLA)and Bayesian Optimization(BO).We compare these simulated quantum results with two established classical optimization methods:Simulated Annealing(SA)and the Gurobi solver.The study focuses on 4×4 grid configurations(requiring 16 qubits),providing insights into near-term quantum algorithm applicability for renewable energy optimization.展开更多
Intense laser light,with its ability to trap small particles,is providing us unprecedented access to the microscopic world.Nevertheless,owing to its open nature,optical force is nonconservative and can only be describ...Intense laser light,with its ability to trap small particles,is providing us unprecedented access to the microscopic world.Nevertheless,owing to its open nature,optical force is nonconservative and can only be described by a non-Hermitian theory.This non-Hermiticity sets such system apart from conventional systems and has offered rich physics,such as the possession of the exceptional points.Consequently,analyzing and demonstrating the dynamics of large optically-bound clusters becomes an intricate challenge.Here,we developed a scalable quantum approach that allows us to predict the trajectories of optically trapped particles and tackle the associated non-Hermitian physics.This approach is based on the linear combination of unitary operations.With this,we experimentally revealed the non-Hermiticity and exceptional point for a single or multiple particles trapped by optical force fields,using a nuclear magnetic resonance quantum processor.Our method’s scalability and stability have offering a promising path for large-scale optical manipulation with non-Hermitian dynamics.展开更多
Quantum computing has grown substantially over the past four decades,but whether it can outperform classical methods in practical use remains uncertain[1].Fluid dynamics simulation,challenging in classical physics but...Quantum computing has grown substantially over the past four decades,but whether it can outperform classical methods in practical use remains uncertain[1].Fluid dynamics simulation,challenging in classical physics but vital for applications,is a potential area for showcasing quantum advantage.The quantum computing for fluid dynamics(QCFD)[2]is expected to efficiently simulate intricate turbulent flows with high Reynolds numbers.This capability is crucial for critical applications,including aircraft design and weather forecast.展开更多
Various phenomena have been observed in molecule-cavity coupled systems,which are believed to hold potential for applications in transistors,lasers,and computational units,among others.However,theoretical methods for ...Various phenomena have been observed in molecule-cavity coupled systems,which are believed to hold potential for applications in transistors,lasers,and computational units,among others.However,theoretical methods for simulating molecules in optical cavities still require further development due to the complex couplings between electrons,phonons,and photons within the cavity.In this study,motivated by recent advances in quantum algorithms and quantum computing hardware,we propose a quantum computing algorithm tailored for molecules in optical cavities.Our method,based on a variational quantum algorithm and variational boson encoders,has its effectiveness validated on both quantum simulators and hardware.For aggregates within the cavity,described by the Holstein-Tavis-Cummings model,our approach demonstrates clear advantages over other quantum and classical methods,as proved by numerical benchmarks.Additionally,we apply this method to study the H2 molecule in a cavity using a superconducting quantum computer and the Pauli-Fierz model.To enhance accuracy,we incorporate error mitigation techniques,such as readout and reference-state error mitigation,resulting in an 86%reduction in the average error.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
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
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
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
Quantum computing is a promising technology that has the potential to revolutionize many areas of science and technology,including communication.In this review,we discuss the current state of quantum computing in comm...Quantum computing is a promising technology that has the potential to revolutionize many areas of science and technology,including communication.In this review,we discuss the current state of quantum computing in communication and its potential applications in various areas such as network optimization,signal processing,and machine learning for communication.First,the basic principle of quantum computing,quantum physics systems,and quantum algorithms are analyzed.Then,based on the classification of quantum algorithms,several important basic quantum algorithms,quantum optimization algorithms,and quantum machine learning algorithms are discussed in detail.Finally,the basic ideas and feasibility of introducing quantum algorithms into communications are emphatically analyzed,which provides a reference to address computational bottlenecks in communication networks.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
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.
文摘As technological innovations in computers begin to advance past their limit (Moore’s law), a new problem arises: What computational device would emerge after the classical supercomputers reach their physical limitations? At this moment in time, quantum computers are at their starting stage and there are already some strengths and advantages when compared with modern, classical computers. In its testing period, there are a variety of ways to create a quantum computer by processes such as the trapped-ion and the spin-dot methods. Nowadays, there are many drawbacks with quantum computers such as issues with decoherence and scalability, but many of these issues are easily emended. Nevertheless, the benefits of quantum computers at the moment outweigh the potential drawbacks. These benefits include its use of many properties of quantum mechanics such as quantum superposition, entanglement, and parallelism. Using these basic properties of quantum mechanics, quantum computers are capable of achieving faster computational times for certain problems such as finding prime factors of an integer by using Shor’s algorithm. From the advantages such as faster computing times in certain situations and higher computing powers than classical computers, quantum computers have a high probability to be the future of computing after classical computers hit their peak.
基金Project supported by the Key Research and Development Program of Guangdong Province,China(Grant No.2018B030326001)the National Natural Science Foundation of China(Grant Nos.61521001,12074179,and 11890704)。
文摘Quantum singular value thresholding(QSVT) algorithm,as a core module of many mathematical models,seeks the singular values of a sparse and low rank matrix exceeding a threshold and their associated singular vectors.The existing all-qubit QSVT algorithm demands lots of ancillary qubits,remaining a huge challenge for realization on nearterm intermediate-scale quantum computers.In this paper,we propose a hybrid QSVT(HQSVT) algorithm utilizing both discrete variables(DVs) and continuous variables(CVs).In our algorithm,raw data vectors are encoded into a qubit system and the following data processing is fulfilled by hybrid quantum operations.Our algorithm requires O [log(MN)] qubits with0(1) qumodes and totally performs 0(1) operations,which significantly reduces the space and runtime consumption.
基金the valuable discussions.Project supported by the National Natural Science Foundation of China(Grant Nos.92265207 and T2121001)Beijing Natural Science Foundation(Grant No.Z200009).
文摘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.
基金supported by the National Key R&D Program of China(Grant Nos.2017YFA0303302 and 2018YFA0305602)the National Natural Science Foundation of China(Grant No.11921005)Shanghai Municipal Science and Technology Major Project(Grant No.2019SHZDZX01)。
文摘A theoretical model of computation is proposed based on Lorentz quantum mechanics.Besides the standard qubits,this model has an additional bit,which we call hyperbolic bit(or hybit in short).A set of basic logical gates are constructed and their universality is proved.As an application,a search algorithm is designed for this computer model and is found to be exponentially faster than Grover's search algorithm.
文摘This paper investigatesWindfarmLayoutOptimization(WFLO),where we formulate turbine placement considering wake effects as a Quadratic Unconstrained Binary Optimization(QUBO)problem.Wind energy plays a critical role in the transition toward sustainable power systems,but the optimal placement of turbines remains a challenging combinatorial problem due to complex wake interactions.With recent advances in quantum computing,there is growing interest in exploring whether hybrid quantum-classical methods can provide advantages for such computationally intensive tasks.We investigate solving the resulting QUBO problem using the Variational Quantum Eigensolver(VQE)implemented onQiskit’s quantum computer simulator,employing a quantum noise-free,gate-based circuit model.Three classical optimizers are discussed,with a detailed analysis of the two most effective approaches:Constrained Optimization BY Linear Approximation(COBYLA)and Bayesian Optimization(BO).We compare these simulated quantum results with two established classical optimization methods:Simulated Annealing(SA)and the Gurobi solver.The study focuses on 4×4 grid configurations(requiring 16 qubits),providing insights into near-term quantum algorithm applicability for renewable energy optimization.
基金supported by the National Key Research and Development Program of China(2019YFA0308100)the National Natural Science Foundation of China(12074169,12104213,12204230)+5 种基金the Guangdong Provincial Key Laboratory(2019B121203002)the Pearl River Talent Recruitment Program(2019QN01X298)Beijing Nova Program under Grants(20230484345,20240484609)Guangdong Province Talent Recruitment Program(2021QN02C103)Research Grants Council of Hong Kong(AoE/P-502/20)the Guangdong Provincial Quantum Science Strategic Initiative(GDZX2303001,GDZX2200001).
文摘Intense laser light,with its ability to trap small particles,is providing us unprecedented access to the microscopic world.Nevertheless,owing to its open nature,optical force is nonconservative and can only be described by a non-Hermitian theory.This non-Hermiticity sets such system apart from conventional systems and has offered rich physics,such as the possession of the exceptional points.Consequently,analyzing and demonstrating the dynamics of large optically-bound clusters becomes an intricate challenge.Here,we developed a scalable quantum approach that allows us to predict the trajectories of optically trapped particles and tackle the associated non-Hermitian physics.This approach is based on the linear combination of unitary operations.With this,we experimentally revealed the non-Hermiticity and exceptional point for a single or multiple particles trapped by optical force fields,using a nuclear magnetic resonance quantum processor.Our method’s scalability and stability have offering a promising path for large-scale optical manipulation with non-Hermitian dynamics.
文摘Quantum computing has grown substantially over the past four decades,but whether it can outperform classical methods in practical use remains uncertain[1].Fluid dynamics simulation,challenging in classical physics but vital for applications,is a potential area for showcasing quantum advantage.The quantum computing for fluid dynamics(QCFD)[2]is expected to efficiently simulate intricate turbulent flows with high Reynolds numbers.This capability is crucial for critical applications,including aircraft design and weather forecast.
基金supported by the National Natural Science Foundation of China(Grant Nos.T2350009 and 22433007)Guangdong Provincial Natural Science Foundation(Grant No.2024A1515011185)+2 种基金the Shenzhen City“Pengcheng Peacock”Talent Program,and Shenzhen Science and Technology Program(No.KQTD20240729102028011)W.L.is supported by the Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)University Development Fund(UDF01003789)。
文摘Various phenomena have been observed in molecule-cavity coupled systems,which are believed to hold potential for applications in transistors,lasers,and computational units,among others.However,theoretical methods for simulating molecules in optical cavities still require further development due to the complex couplings between electrons,phonons,and photons within the cavity.In this study,motivated by recent advances in quantum algorithms and quantum computing hardware,we propose a quantum computing algorithm tailored for molecules in optical cavities.Our method,based on a variational quantum algorithm and variational boson encoders,has its effectiveness validated on both quantum simulators and hardware.For aggregates within the cavity,described by the Holstein-Tavis-Cummings model,our approach demonstrates clear advantages over other quantum and classical methods,as proved by numerical benchmarks.Additionally,we apply this method to study the H2 molecule in a cavity using a superconducting quantum computer and the Pauli-Fierz model.To enhance accuracy,we incorporate error mitigation techniques,such as readout and reference-state error mitigation,resulting in an 86%reduction in the average error.
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.
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.
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.
文摘Quantum computing is a promising technology that has the potential to revolutionize many areas of science and technology,including communication.In this review,we discuss the current state of quantum computing in communication and its potential applications in various areas such as network optimization,signal processing,and machine learning for communication.First,the basic principle of quantum computing,quantum physics systems,and quantum algorithms are analyzed.Then,based on the classification of quantum algorithms,several important basic quantum algorithms,quantum optimization algorithms,and quantum machine learning algorithms are discussed in detail.Finally,the basic ideas and feasibility of introducing quantum algorithms into communications are emphatically analyzed,which provides a reference to address computational bottlenecks in communication networks.
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.
