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
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
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
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
In this letter,we propose a duality computing mode,which resembles particle-wave duality property whena quantum system such as a quantum computer passes through a double-slit.In this mode,computing operations arenot n...In this letter,we propose a duality computing mode,which resembles particle-wave duality property whena quantum system such as a quantum computer passes through a double-slit.In this mode,computing operations arenot necessarily unitary.The duality mode provides a natural link between classical computing and quantum computing.In addition,the duality mode provides a new tool for quantum algorithm design.展开更多
Shor proposed a quantum polynomial-time integer factorization algorithm to break the RSA public-key cryptosystem.In this paper,we propose a new quantum algorithm for breaking RSA by computing the order of the RSA ciph...Shor proposed a quantum polynomial-time integer factorization algorithm to break the RSA public-key cryptosystem.In this paper,we propose a new quantum algorithm for breaking RSA by computing the order of the RSA ciphertext C.The new algorithm has the following properties：1）recovering the RSA plaintext M from the ciphertext C without factoring n; 2）avoiding the even order of the element; 3）having higher success probability than Shor＇s; 4）having the same complexity as Shor＇s.展开更多
The quantum nature of bulk ensemble NMR quantum computing the center of recent heated debate,is addressed. Concepts of the mixed state and entanglement are examined, and the data in a two-qubit liquid NMRquantum compu...The quantum nature of bulk ensemble NMR quantum computing the center of recent heated debate,is addressed. Concepts of the mixed state and entanglement are examined, and the data in a two-qubit liquid NMRquantum computation are analyzed. The main points in this paper are: i) Density matrix describes the "state" of anaverage particle in an ensemble. It does not describe the state of an individual particle in an ensemble; ii) Entanglementis a property of the wave function of a microscopic particle (such as a molecule in a liquid NMR sample), and separabilityof the density matrix cannot be used to measure the entanglement of mixed ensemble; iii) The state evolution in bulk-ensemble NMRquantum computation is quantum-mechanical; iv) The coefficient before the effective pure state densitymatrix, e, is a measure of the simultaneity of the molecules in an ensemble. It reflects the intensity of the NMR signaland has no significance in quantifying the entanglement in the bulk ensemble NMR system. The decomposition of thedensity matrix into product states is only an indication that the ensemble can be prepared by an ensemble with theparticles unentangled. We conclude that effective-pure-state NMR quantum computation is genuine, not just classicalsimulations.展开更多
Nuclear physics,whose underling theory is described by quantum gauge field coupled with matter,is fundamentally important and yet is formidably challenge for simulation with classical computers.Quantum computing provi...Nuclear physics,whose underling theory is described by quantum gauge field coupled with matter,is fundamentally important and yet is formidably challenge for simulation with classical computers.Quantum computing provides a perhaps transformative approach for studying and understanding nuclear physics.With rapid scaling-up of quantum processors as well as advances on quantum algorithms,the digital quantum simulation approach for simulating quantum gauge fields and nuclear physics has gained lots of attention.In this review,we aim to summarize recent efforts on solving nuclear physics with quantum computers.We first discuss a formulation of nuclear physics in the language of quantum computing.In particular,we review how quantum gauge fields(both Abelian and non-Abelian)and their coupling to matter field can be mapped and studied on a quantum computer.We then introduce related quantum algorithms for solving static properties and real-time evolution for quantum systems,and show their applications for a broad range of problems in nuclear physics,including simulation of lattice gauge field,solving nucleon and nuclear structures,quantum advantage for simulating scattering in quantum field theory,non-equilibrium dynamics,and so on.Finally,a short outlook on future work is given.展开更多
The quantum nature of bulk ensemble NMR quantum computing — the center of recent heated debate, is addressed. Concepts of the mixed state and entanglement are examined, and the data in a two-qubit liquid NMR quantum ...The quantum nature of bulk ensemble NMR quantum computing — the center of recent heated debate, is addressed. Concepts of the mixed state and entanglement are examined, and the data in a two-qubit liquid NMR quantum computation are analyzed. The main points in this paper are: i) Density matrix describes the 'state' of an average particle in an ensemble. It does not describe the state of an individual particle in an ensemble; ii) Entanglement is a property of the wave function of a microscopic particle (such as a molecule in a liquid NMR sample), and separability of the density matrix cannot be used to measure the entanglement of mixed ensemble; iii) The state evolution in bulk-ensemble NMR quantum computation is quantum-mechanical; iv) The coefficient before the effective pure state density matrix, ?, is a measure of the simultaneity of the molecules in an ensemble. It reflects the intensity of the NMR signal and has no significance in quantifying the entanglement in the bulk ensemble NMR system. The decomposition of the density matrix into product states is only an indication that the ensemble can be prepared by an ensemble with the particles unentangled. We conclude that effective-pure-state NMR quantum computation is genuine, not just classical simulations.展开更多
Unravelling the source of quantum computing power has been a major goal in the field of quantum information science.In recent years,the quantum resource theory(QRT)has been established to characterize various quantum ...Unravelling the source of quantum computing power has been a major goal in the field of quantum information science.In recent years,the quantum resource theory(QRT)has been established to characterize various quantum resources,yet their roles in quantum computing tasks still require investigation.The so-called universal quantum computing model(UQCM),e.g.the circuit model,has been the main framework to guide the design of quantum algorithms,creation of real quantum computers etc.In this work,we combine the study of UQCM together with QRT.We find,on one hand,using QRT can provide a resource-theoretic characterization of a UQCM,the relation among models and inspire new ones,and on the other hand,using UQCM offers a framework to apply resources,study relation among these resources and classify them.We develop the theory of universal resources in the setting of UQCM,and find a rich spectrum of UQCMs and the corresponding universal resources.Depending on a hierarchical structure of resource theories,we find models can be classified into families.In this work,we study three natural families of UQCMs in detail:the amplitude family,the quasi-probability family,and the Hamiltonian family.They include some well known models,like the measurement-based model and adiabatic model,and also inspire new models such as the contextual model that we introduce.Each family contains at least a triplet of models,and such a succinct structure of families of UQCMs offers a unifying picture to investigate resources and design models.It also provides a rigorous framework to resolve puzzles,such as the role of entanglement versus interference,and unravel resource-theoretic features of quantum algorithms.展开更多
We introduce a new scalable cavity quantum electrodynamics platform which can be used for quantum computing. This system is composed of coupled photonic crystal (PC) cavities which their modes lie on a Dirac cone in t...We introduce a new scalable cavity quantum electrodynamics platform which can be used for quantum computing. This system is composed of coupled photonic crystal (PC) cavities which their modes lie on a Dirac cone in the whole super crystal band structure. Quantum information is stored in quantum dots that are positioned inside the cavities. We show if there is just one quantum dot in the system, energy as photon is exchanged between the quantum dot and the Dirac modes sinusoidally. Meanwhile the quantum dot becomes entangled with Dirac modes. If we insert more quantum dots into the system, they also become entangled with each other.展开更多
We describe a scheme for universal quantum computation with Majorana fermions. We investigate two possible dissipative couplings of Majorana fermions to external systems, including metallic leads and local phonons. Wh...We describe a scheme for universal quantum computation with Majorana fermions. We investigate two possible dissipative couplings of Majorana fermions to external systems, including metallic leads and local phonons. While the dissipation when coupling to metallic leads to uninteresting states for the Majorana fermions, we show that coupling the Majorana fermions to local phonons allows to generate arbitrary dissipations and therefore universal quantum operations on a single QuBit that can be enhanced by additional two-QuBit operations.展开更多
Electric power systems provide the backbone of modern industrial societies.Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems.However,today’s power ...Electric power systems provide the backbone of modern industrial societies.Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems.However,today’s power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources,as well as managing huge volumes of data accordingly.These unprecedented challenges call for transformative analytics to support the resilient operations of power systems.Recently,the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations.Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems,which may lead to ultra-scalable and efficient power grid analytics.This paper reviews the newly emerging application of quantum computing techniques in power systems.We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives,including static analysis,transient analysis,stochastic analysis,optimization,stability,and control.We thoroughly discuss the related quantum algorithms,their benefits and limitations,hardware implementations,and recommended practices.We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era.Finally,we discuss challenges and future research directions.This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids.展开更多
Quantum Computing and Quantum Information Science seem very promising and developing rapidly since its inception in early 1980s by Paul Benioff with the proposal of quantum mechanical model of the Turing machine and l...Quantum Computing and Quantum Information Science seem very promising and developing rapidly since its inception in early 1980s by Paul Benioff with the proposal of quantum mechanical model of the Turing machine and later By Richard Feynman and Yuri Manin for the proposal of a quantum computers for simulating various problems that classical computer could not.Quantum computers have a computational advantage for some problems,over classical computers and most applications are trying to use an efficient combination of classical and quantum computers like Shor’s factoring algorithm.Other areas that are expected to be benefitted from quantum computing are Machine Learning and deep learning,molecular biology,genomics and cancer research,space exploration,atomic and nuclear research and macro-economic forecasting.This paper represents a brief overview of the state of art of quantum computing and quantum information science with discussions of various theoretical and experimental aspects adopted by the researchers.展开更多
The potential impact of quantum computing on various industries such as finance, healthcare, cryptography, and transportation is significant;therefore, sectors face challenges in understanding where to start because o...The potential impact of quantum computing on various industries such as finance, healthcare, cryptography, and transportation is significant;therefore, sectors face challenges in understanding where to start because of the complex nature of this technology. Starting early to explore what is supposed to be done is crucial for providing sectors with the necessary knowledge, tools, and processes to keep pace with rapid advancements in quantum computing. This article emphasizes the importance of consultancy and governance solutions that aid sectors in preparing for the quantum computing revolution. The article begins by discussing the reasons why sectors need to be prepared for quantum computing and emphasizes the importance of proactive preparation. It illustrates this point by providing a real-world example of a partnership. Subsequently, the article mentioned the benefits of quantum computing readiness, including increased competitiveness, improved security, and structured data. In addition, this article discusses the steps that various sectors can take to achieve quantum readiness, considering the potential risks and opportunities in industries. The proposed solutions for achieving quantum computing readiness include establishing a quantum computing office, contracting with major quantum computing companies, and learning from quantum computing organizations. This article provides the detailed advantages and disadvantages of each of these steps and emphasizes the need to carefully evaluate their potential drawbacks to ensure that they align with the sector’s unique needs, goals, and available resources. Finally, this article proposes various solutions and recommendations for sectors to achieve quantum-computing readiness.展开更多
The well-known Riccati differential equations play a key role in many fields,including problems in protein folding,control and stabilization,stochastic control,and cybersecurity(risk analysis and malware propaga-tion)...The well-known Riccati differential equations play a key role in many fields,including problems in protein folding,control and stabilization,stochastic control,and cybersecurity(risk analysis and malware propaga-tion).Quantum computer algorithms have the potential to implement faster approximate solutions to the Riccati equations compared with strictly classical algorithms.While systems with many qubits are still under development,there is significant interest in developing algorithms for near-term quantum computers to determine their accuracy and limitations.In this paper,we propose a hybrid quantum-classical algorithm,the Matrix Riccati Solver(MRS).This approach uses a transformation of variables to turn a set of nonlinear differential equation into a set of approximate linear differential equations(i.e.,second order non-constant coefficients)which can in turn be solved using a version of the Harrow-Hassidim-Lloyd(HHL)quantum algorithm for the case of Hermitian matrices.We implement this approach using the Qiskit language and compute near-term results using a 4 qubit IBM Q System quantum computer.Comparisons with classical results and areas for future research are discussed.展开更多
In this study,we investigate the ef-ficacy of a hybrid parallel algo-rithm aiming at enhancing the speed of evaluation of two-electron repulsion integrals(ERI)and Fock matrix generation on the Hygon C86/DCU(deep compu...In this study,we investigate the ef-ficacy of a hybrid parallel algo-rithm aiming at enhancing the speed of evaluation of two-electron repulsion integrals(ERI)and Fock matrix generation on the Hygon C86/DCU(deep computing unit)heterogeneous computing platform.Multiple hybrid parallel schemes are assessed using a range of model systems,including those with up to 1200 atoms and 10000 basis func-tions.The findings of our research reveal that,during Hartree-Fock(HF)calculations,a single DCU ex-hibits 33.6 speedups over 32 C86 CPU cores.Compared with the efficiency of Wuhan Electronic Structure Package on Intel X86 and NVIDIA A100 computing platform,the Hygon platform exhibits good cost-effective-ness,showing great potential in quantum chemistry calculation and other high-performance scientific computations.展开更多
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
Adiabatic holonomic gates possess the geometric robustness of adiabatic geometric phases,i.e.,dependence only on the evolution path of the parameter space but not on the evolution details of the quantum system,which,w...Adiabatic holonomic gates possess the geometric robustness of adiabatic geometric phases,i.e.,dependence only on the evolution path of the parameter space but not on the evolution details of the quantum system,which,when coordinated with decoherence-free subspaces,permits additional resilience to the collective dephasing environment.However,the previous scheme[Phys.Rev.Lett.95130501(2005)]of adiabatic holonomic quantum computation in decoherence-free subspaces requires four-body interaction that is challenging in practical implementation.In this work,we put forward a scheme to realize universal adiabatic holonomic quantum computation in decoherence-free subspaces using only realistically available two-body interaction,thereby avoiding the difficulty of implementing four-body interaction.Furthermore,an arbitrary one-qubit gate in our scheme can be realized by a single-shot implementation,which eliminates the need to combine multiple gates for realizing such a gate.展开更多
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.
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 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.
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the National Fundamental Research Program under Grant No.2006CB921106National Natural Science Foundation of China under Grant Nos.10325521 and 60433050
文摘In this letter,we propose a duality computing mode,which resembles particle-wave duality property whena quantum system such as a quantum computer passes through a double-slit.In this mode,computing operations arenot necessarily unitary.The duality mode provides a natural link between classical computing and quantum computing.In addition,the duality mode provides a new tool for quantum algorithm design.
基金Supported by the National Natural Science Foundation of China(61303212,61202386)the State Key Program of National Natural Science of China(61332019)the Major Research Plan of the National Natural Science Foundation of China(91018008,SKLSE-2015-A-02)
文摘Shor proposed a quantum polynomial-time integer factorization algorithm to break the RSA public-key cryptosystem.In this paper,we propose a new quantum algorithm for breaking RSA by computing the order of the RSA ciphertext C.The new algorithm has the following properties：1）recovering the RSA plaintext M from the ciphertext C without factoring n; 2）avoiding the even order of the element; 3）having higher success probability than Shor＇s; 4）having the same complexity as Shor＇s.
基金The project supported by National Fundamental Research Program under Grant No. 001CB309308, and National Natural Science Foundation of China under Grant No. 60073009, the Hang Tian Science Fund, and the Excellent Young University Teachers' Fund of the Education Ministry of Chnia
文摘The quantum nature of bulk ensemble NMR quantum computing the center of recent heated debate,is addressed. Concepts of the mixed state and entanglement are examined, and the data in a two-qubit liquid NMRquantum computation are analyzed. The main points in this paper are: i) Density matrix describes the "state" of anaverage particle in an ensemble. It does not describe the state of an individual particle in an ensemble; ii) Entanglementis a property of the wave function of a microscopic particle (such as a molecule in a liquid NMR sample), and separabilityof the density matrix cannot be used to measure the entanglement of mixed ensemble; iii) The state evolution in bulk-ensemble NMRquantum computation is quantum-mechanical; iv) The coefficient before the effective pure state densitymatrix, e, is a measure of the simultaneity of the molecules in an ensemble. It reflects the intensity of the NMR signaland has no significance in quantifying the entanglement in the bulk ensemble NMR system. The decomposition of thedensity matrix into product states is only an indication that the ensemble can be prepared by an ensemble with theparticles unentangled. We conclude that effective-pure-state NMR quantum computation is genuine, not just classicalsimulations.
基金Project supported by the Key-Area Research and Development Program of Guang Dong Province,China(Grant No.2019B030330001)Guangdong Major Project of Basic and Applied Basic Research(Grant No.2020B0301030008)+2 种基金the National Natural Science Foundation of China(Grant Nos.12074180,12005065,12022512,and 12035007)the Key Project of Science and Technology of Guangzhou(Grant Nos.201804020055 and 2019050001)the National Key Research and Development Program of China(Grant No.2016YFA0301800)。
文摘Nuclear physics,whose underling theory is described by quantum gauge field coupled with matter,is fundamentally important and yet is formidably challenge for simulation with classical computers.Quantum computing provides a perhaps transformative approach for studying and understanding nuclear physics.With rapid scaling-up of quantum processors as well as advances on quantum algorithms,the digital quantum simulation approach for simulating quantum gauge fields and nuclear physics has gained lots of attention.In this review,we aim to summarize recent efforts on solving nuclear physics with quantum computers.We first discuss a formulation of nuclear physics in the language of quantum computing.In particular,we review how quantum gauge fields(both Abelian and non-Abelian)and their coupling to matter field can be mapped and studied on a quantum computer.We then introduce related quantum algorithms for solving static properties and real-time evolution for quantum systems,and show their applications for a broad range of problems in nuclear physics,including simulation of lattice gauge field,solving nucleon and nuclear structures,quantum advantage for simulating scattering in quantum field theory,non-equilibrium dynamics,and so on.Finally,a short outlook on future work is given.
文摘The quantum nature of bulk ensemble NMR quantum computing — the center of recent heated debate, is addressed. Concepts of the mixed state and entanglement are examined, and the data in a two-qubit liquid NMR quantum computation are analyzed. The main points in this paper are: i) Density matrix describes the 'state' of an average particle in an ensemble. It does not describe the state of an individual particle in an ensemble; ii) Entanglement is a property of the wave function of a microscopic particle (such as a molecule in a liquid NMR sample), and separability of the density matrix cannot be used to measure the entanglement of mixed ensemble; iii) The state evolution in bulk-ensemble NMR quantum computation is quantum-mechanical; iv) The coefficient before the effective pure state density matrix, ?, is a measure of the simultaneity of the molecules in an ensemble. It reflects the intensity of the NMR signal and has no significance in quantifying the entanglement in the bulk ensemble NMR system. The decomposition of the density matrix into product states is only an indication that the ensemble can be prepared by an ensemble with the particles unentangled. We conclude that effective-pure-state NMR quantum computation is genuine, not just classical simulations.
基金funded by the National Natural Science Foundation of China under Grants Nos.12047503 and 12105343.
文摘Unravelling the source of quantum computing power has been a major goal in the field of quantum information science.In recent years,the quantum resource theory(QRT)has been established to characterize various quantum resources,yet their roles in quantum computing tasks still require investigation.The so-called universal quantum computing model(UQCM),e.g.the circuit model,has been the main framework to guide the design of quantum algorithms,creation of real quantum computers etc.In this work,we combine the study of UQCM together with QRT.We find,on one hand,using QRT can provide a resource-theoretic characterization of a UQCM,the relation among models and inspire new ones,and on the other hand,using UQCM offers a framework to apply resources,study relation among these resources and classify them.We develop the theory of universal resources in the setting of UQCM,and find a rich spectrum of UQCMs and the corresponding universal resources.Depending on a hierarchical structure of resource theories,we find models can be classified into families.In this work,we study three natural families of UQCMs in detail:the amplitude family,the quasi-probability family,and the Hamiltonian family.They include some well known models,like the measurement-based model and adiabatic model,and also inspire new models such as the contextual model that we introduce.Each family contains at least a triplet of models,and such a succinct structure of families of UQCMs offers a unifying picture to investigate resources and design models.It also provides a rigorous framework to resolve puzzles,such as the role of entanglement versus interference,and unravel resource-theoretic features of quantum algorithms.
文摘We introduce a new scalable cavity quantum electrodynamics platform which can be used for quantum computing. This system is composed of coupled photonic crystal (PC) cavities which their modes lie on a Dirac cone in the whole super crystal band structure. Quantum information is stored in quantum dots that are positioned inside the cavities. We show if there is just one quantum dot in the system, energy as photon is exchanged between the quantum dot and the Dirac modes sinusoidally. Meanwhile the quantum dot becomes entangled with Dirac modes. If we insert more quantum dots into the system, they also become entangled with each other.
文摘We describe a scheme for universal quantum computation with Majorana fermions. We investigate two possible dissipative couplings of Majorana fermions to external systems, including metallic leads and local phonons. While the dissipation when coupling to metallic leads to uninteresting states for the Majorana fermions, we show that coupling the Majorana fermions to local phonons allows to generate arbitrary dissipations and therefore universal quantum operations on a single QuBit that can be enhanced by additional two-QuBit operations.
基金supported in part by the Advanced Grid Modeling Program under U.S.Department of Energy’s Office of Electricity under Agreement No.37533(P.Z.)in part by Stony Brook Uni-versity’s Office of the Vice President for Research through a Quantum Information Science and Technology Seed Grant(P.Z.)in part by the National Science Foundation under Grant No.PHY 1915165(T.-C.W.).
文摘Electric power systems provide the backbone of modern industrial societies.Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems.However,today’s power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources,as well as managing huge volumes of data accordingly.These unprecedented challenges call for transformative analytics to support the resilient operations of power systems.Recently,the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations.Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems,which may lead to ultra-scalable and efficient power grid analytics.This paper reviews the newly emerging application of quantum computing techniques in power systems.We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives,including static analysis,transient analysis,stochastic analysis,optimization,stability,and control.We thoroughly discuss the related quantum algorithms,their benefits and limitations,hardware implementations,and recommended practices.We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era.Finally,we discuss challenges and future research directions.This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids.
文摘Quantum Computing and Quantum Information Science seem very promising and developing rapidly since its inception in early 1980s by Paul Benioff with the proposal of quantum mechanical model of the Turing machine and later By Richard Feynman and Yuri Manin for the proposal of a quantum computers for simulating various problems that classical computer could not.Quantum computers have a computational advantage for some problems,over classical computers and most applications are trying to use an efficient combination of classical and quantum computers like Shor’s factoring algorithm.Other areas that are expected to be benefitted from quantum computing are Machine Learning and deep learning,molecular biology,genomics and cancer research,space exploration,atomic and nuclear research and macro-economic forecasting.This paper represents a brief overview of the state of art of quantum computing and quantum information science with discussions of various theoretical and experimental aspects adopted by the researchers.
文摘The potential impact of quantum computing on various industries such as finance, healthcare, cryptography, and transportation is significant;therefore, sectors face challenges in understanding where to start because of the complex nature of this technology. Starting early to explore what is supposed to be done is crucial for providing sectors with the necessary knowledge, tools, and processes to keep pace with rapid advancements in quantum computing. This article emphasizes the importance of consultancy and governance solutions that aid sectors in preparing for the quantum computing revolution. The article begins by discussing the reasons why sectors need to be prepared for quantum computing and emphasizes the importance of proactive preparation. It illustrates this point by providing a real-world example of a partnership. Subsequently, the article mentioned the benefits of quantum computing readiness, including increased competitiveness, improved security, and structured data. In addition, this article discusses the steps that various sectors can take to achieve quantum readiness, considering the potential risks and opportunities in industries. The proposed solutions for achieving quantum computing readiness include establishing a quantum computing office, contracting with major quantum computing companies, and learning from quantum computing organizations. This article provides the detailed advantages and disadvantages of each of these steps and emphasizes the need to carefully evaluate their potential drawbacks to ensure that they align with the sector’s unique needs, goals, and available resources. Finally, this article proposes various solutions and recommendations for sectors to achieve quantum-computing readiness.
文摘The well-known Riccati differential equations play a key role in many fields,including problems in protein folding,control and stabilization,stochastic control,and cybersecurity(risk analysis and malware propaga-tion).Quantum computer algorithms have the potential to implement faster approximate solutions to the Riccati equations compared with strictly classical algorithms.While systems with many qubits are still under development,there is significant interest in developing algorithms for near-term quantum computers to determine their accuracy and limitations.In this paper,we propose a hybrid quantum-classical algorithm,the Matrix Riccati Solver(MRS).This approach uses a transformation of variables to turn a set of nonlinear differential equation into a set of approximate linear differential equations(i.e.,second order non-constant coefficients)which can in turn be solved using a version of the Harrow-Hassidim-Lloyd(HHL)quantum algorithm for the case of Hermitian matrices.We implement this approach using the Qiskit language and compute near-term results using a 4 qubit IBM Q System quantum computer.Comparisons with classical results and areas for future research are discussed.
基金supported by the National Natural Science Foundation of China(No.22373112 to Ji Qi,No.22373111 and 21921004 to Minghui Yang)GH-fund A(No.202107011790)。
文摘In this study,we investigate the ef-ficacy of a hybrid parallel algo-rithm aiming at enhancing the speed of evaluation of two-electron repulsion integrals(ERI)and Fock matrix generation on the Hygon C86/DCU(deep computing unit)heterogeneous computing platform.Multiple hybrid parallel schemes are assessed using a range of model systems,including those with up to 1200 atoms and 10000 basis func-tions.The findings of our research reveal that,during Hartree-Fock(HF)calculations,a single DCU ex-hibits 33.6 speedups over 32 C86 CPU cores.Compared with the efficiency of Wuhan Electronic Structure Package on Intel X86 and NVIDIA A100 computing platform,the Hygon platform exhibits good cost-effective-ness,showing great potential in quantum chemistry calculation and other high-performance scientific computations.
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.
基金Project supported by the National Natural Science Foundation of China(Grant No.12305021)。
文摘Adiabatic holonomic gates possess the geometric robustness of adiabatic geometric phases,i.e.,dependence only on the evolution path of the parameter space but not on the evolution details of the quantum system,which,when coordinated with decoherence-free subspaces,permits additional resilience to the collective dephasing environment.However,the previous scheme[Phys.Rev.Lett.95130501(2005)]of adiabatic holonomic quantum computation in decoherence-free subspaces requires four-body interaction that is challenging in practical implementation.In this work,we put forward a scheme to realize universal adiabatic holonomic quantum computation in decoherence-free subspaces using only realistically available two-body interaction,thereby avoiding the difficulty of implementing four-body interaction.Furthermore,an arbitrary one-qubit gate in our scheme can be realized by a single-shot implementation,which eliminates the need to combine multiple gates for realizing such a gate.
