Journal articles: 'Application of quantum computing'

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Yang, Hong, Jingjing Wang, and Xu Sun. "Research on Quantum Computing Standard System Architecture and Roadmap." Journal of Physics: Conference Series 2433, no. 1 (February 1, 2023): 012035. http://dx.doi.org/10.1088/1742-6596/2433/1/012035.

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Abstract Quantum computing is an important branch of quantum information technology. Quantum computing is far more powerful than traditional computing in solving some problems, and it has great potential for commercial and military applications. Firstly, this paper introduces the status quo of quantum computing research and the status of domestic and foreign standards, and then discusses the demands of quantum computing standards, and expounds on the necessity of a quantum computing standard system. Then give the quantum computing architecture standard system diagram. Finally, there is a roadmap for Quantum computing standardization is given, including the short, medium and long term. The architecture and the roadmap will be helpful to guide the standardization work as well as the application development.

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Henriet, Loïc, Lucas Beguin, Adrien Signoles, Thierry Lahaye, Antoine Browaeys, Georges-Olivier Reymond, and Christophe Jurczak. "Quantum computing with neutral atoms." Quantum 4 (September 21, 2020): 327. http://dx.doi.org/10.22331/q-2020-09-21-327.

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The manipulation of neutral atoms by light is at the heart of countless scientific discoveries in the field of quantum physics in the last three decades. The level of control that has been achieved at the single particle level within arrays of optical traps, while preserving the fundamental properties of quantum matter (coherence, entanglement, superposition), makes these technologies prime candidates to implement disruptive computation paradigms. In this paper, we review the main characteristics of these devices from atoms / qubits to application interfaces, and propose a classification of a wide variety of tasks that can already be addressed in a computationally efficient manner in the Noisy Intermediate Scale Quantum\cite{Preskill_NISQ} era we are in. We illustrate how applications ranging from optimization challenges to simulation of quantum systems can be explored either at the digital level (programming gate-based circuits) or at the analog level (programming Hamiltonian sequences). We give evidence of the intrinsic scalability of neutral atom quantum processors in the 100-1,000 qubits range and introduce prospects for universal fault tolerant quantum computing and applications beyond quantum computing.

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Peleshenko, Vitaly A. "INTEL-QS QUANTUM COMPUTING." SOFT MEASUREMENTS AND COMPUTING 7/1, no. 56 (2022): 58–64. http://dx.doi.org/10.36871/2618-9976.2022.07.006.

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The article is devoted to quantum processors and quantum programming languages. In particular, the features of technical processes and physical principles of operation and creation of the CPU are considered. The possibilities of practical application of the Intel-QS quantum computing language are considered.

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Morimae, Tomoyuki. "Quantum randomized encoding, verification of quantum computing, no-cloning, and blind quantum computing." Quantum Information and Computation 21, no. 13&14 (September 2021): 1111–34. http://dx.doi.org/10.26421/qic21.13-14-3.

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Randomized encoding is a powerful cryptographic primitive with various applications such as secure multiparty computation, verifiable computation, parallel cryptography, and complexity lower bounds. Intuitively, randomized encoding $\hat{f}$ of a function $f$ is another function such that $f(x)$ can be recovered from $\hat{f}(x)$, and nothing except for $f(x)$ is leaked from $\hat{f}(x)$. Its quantum version, quantum randomized encoding, has been introduced recently [Brakerski and Yuen, arXiv:2006.01085]. Intuitively, quantum randomized encoding $\hat{F}$ of a quantum operation $F$ is another quantum operation such that, for any quantum state $\rho$, $F(\rho)$ can be recovered from $\hat{F}(\rho)$, and nothing except for $F(\rho)$ is leaked from $\hat{F}(\rho)$. In this paper, we show three results. First, we show that if quantum randomized encoding of BB84 state generations is possible with an encoding operation $E$, then a two-round verification of quantum computing is possible with a classical verifier who can additionally do the operation $E$. One of the most important goals in the field of the verification of quantum computing is to construct a verification protocol with a verifier as classical as possible. This result therefore demonstrates a potential application of quantum randomized encoding to the verification of quantum computing: if we can find a good quantum randomized encoding (in terms of the encoding complexity), then we can construct a good verification protocol of quantum computing. Our second result is, however, to show that too good quantum randomized encoding is impossible: if quantum randomized encoding for the generation of even simple states (such as BB84 states) is possible with a classical encoding operation, then the no-cloning is violated. Finally, we consider a natural modification of blind quantum computing protocols in such a way that the server gets the output like quantum randomized encoding. We show that the modified protocol is not secure.

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Williams, Colin, Pieter Kok, Hwang Lee, and Jonathan P. Dowling. "Quantum lithography: A non-computing application of quantum information." Informatik - Forschung und Entwicklung 21, no. 1-2 (September 26, 2006): 73–82. http://dx.doi.org/10.1007/s00450-006-0017-6.

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Sibi, Alex. "The Impact of Quantum Computing on Cryptography." International Journal for Research in Applied Science and Engineering Technology 11, no. 3 (March 31, 2023): 1762–65. http://dx.doi.org/10.22214/ijraset.2023.49770.

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Abstract: The purpose of this paper's abstract is to explain how quantum computing works in terms of current cryptography and to provide the reader a rudimentary understanding of post-quantum algorithms. Community key encoding methods affected, symmetric structures affected, the influence on hash purposes, upright quantum cryptography, distinctions amongst quantum and standard computing, obstacles in quantum computation, and quantum procedures (Shor's and Grover's). The PostQuantum Cryptography section specifically discusses various mathematically based quantum crucial circulation techniques, lattice-built cryptography, multivariate-built cryptography, hash-based signs, and code-based encoding. One of the modern technologies in today's society is quantum computation. The advance of quantum computing applications is the focus of numerous communities and research institutions worldwide. Another developing field at the moment that is becoming stable is artificial intelligence. The major goal of this work is to determine the effects of the development of quantum computing research on applications involving artificial intelligence. Hence, computational methods are utilised in the study's methodology. So that this study's findings about the expanding impact of quantum computing research for a particular application of artificial intelligence can be drawn. The impact and potential of quantum computing on the subject of artificial intelligence is also discussed in this study, along with how quantum computing affects that discipline.

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CR, Senise Jr. "The (Present) Age of Quantum Computing." Physical Science & Biophysics Journal 7, no. 1 (January 5, 2023): 1–3. http://dx.doi.org/10.23880/psbj-16000229.

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Quantum computing is an intense and challenging research area, that promises to change the world we live in. But what is its current status, both in terms of understanding and applications? We discuss some points related to this question in this article.

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Griol-Barres, Israel, Sergio Milla, Antonio Cebrián, Yashar Mansoori, and José Millet. "Variational Quantum Circuits for Machine Learning. An Application for the Detection of Weak Signals." Applied Sciences 11, no. 14 (July 12, 2021): 6427. http://dx.doi.org/10.3390/app11146427.

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Quantum computing is a new paradigm for a multitude of computing applications. This study presents the technologies that are currently available for the physical implementation of qubits and quantum gates, establishing their main advantages and disadvantages and the available frameworks for programming and implementing quantum circuits. One of the main applications for quantum computing is the development of new algorithms for machine learning. In this study, an implementation of a quantum circuit based on support vector machines (SVMs) is described for the resolution of classification problems. This circuit is specially designed for the noisy intermediate-scale quantum (NISQ) computers that are currently available. As an experiment, the circuit is tested on a real quantum computer based on superconducting qubits for an application to detect weak signals of the future. Weak signals are indicators of incipient changes that will have a future impact. Even for experts, the detection of these events is complicated since it is too early to predict this impact. The data obtained with the experiment shows promising results but also confirms that ongoing technological development is still required to take full advantage of quantum computing.

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Magomadov, V. S. "Exploring the current state and application of quantum computing." Journal of Physics: Conference Series 2373, no. 5 (December 1, 2022): 052011. http://dx.doi.org/10.1088/1742-6596/2373/5/052011.

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Abstract This paper is focused on the field of quantum computing which is an important area of research these days. The paper gives a brief history of this phenomenon and discusses how it has been developing since its conception. Furthermore, the paper describes the principles on which the quantity computer is built, such as qubits, entanglement, and superposition. It also discusses the necessity to build a quantum computer and how it could an improvement upon the existing computers. In addition, the paper covers some of the fields in which quantum computing could be particularly beneficial. Finally, some of the problems and challenges associated with the development of quantum computing are addressed.

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Amundson, James, and Elizabeth Sexton-Kennedy. "Quantum Computing." EPJ Web of Conferences 214 (2019): 09010. http://dx.doi.org/10.1051/epjconf/201921409010.

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In recent years Quantum Computing has attracted a great deal of attention in the scientific and technical communities. Interest in the field has expanded to include the popular press and various funding agencies. We discuss the origins of the idea of using quantum systems for computing. We then give an overview in recent developments in quantum hardware and software, as well as some potential applications for high energy physics.

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Gao, Fang, and Guojian Wu. "Application of Quantum Computing in Power Systems." Energies 16, no. 5 (February 25, 2023): 2240. http://dx.doi.org/10.3390/en16052240.

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Liu, Xiaonan, Haoshan Xie, Zhengyu Liu, and Chenyan Zhao. "Survey on the Improvement and Application of HHL Algorithm." Journal of Physics: Conference Series 2333, no. 1 (August 1, 2022): 012023. http://dx.doi.org/10.1088/1742-6596/2333/1/012023.

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Abstract Quantum computing is a new computing mode that follows the laws of quantum mechanics to control quantum information units for computation. In terms of computational efficiency, due to the existence of quantum mechanical superposition, some known quantum algorithms can process problems faster than traditional general-purpose computers. HHL algorithm is an algorithm for solving linear system problems. Compared with classical algorithms in solving linear equations, it has an exponential acceleration effect in certain cases and as a sub-module, it is widely used in some machine learning algorithms to form quantum machines learning algorithms. However, there are some limiting factors in the use of this algorithm, which affect the overall effect of the algorithm. How to improve it to make the algorithm perform better has become an important issue in the field of quantum computing. This paper summarizes the optimization and improvement of HHL algorithm since it was proposed, and the application of HHL algorithm in machine learning, and discusses some possible future improvements of some subroutines in HHL algorithm.

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Ur Rasool, Raihan, Hafiz Farooq Ahmad, Wajid Rafique, Adnan Qayyum, Junaid Qadir, and Zahid Anwar. "Quantum Computing for Healthcare: A Review." Future Internet 15, no. 3 (February 27, 2023): 94. http://dx.doi.org/10.3390/fi15030094.

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In recent years, the interdisciplinary field of quantum computing has rapidly developed and garnered substantial interest from both academia and industry due to its ability to process information in fundamentally different ways, leading to hitherto unattainable computational capabilities. However, despite its potential, the full extent of quantum computing’s impact on healthcare remains largely unexplored. This survey paper presents the first systematic analysis of the various capabilities of quantum computing in enhancing healthcare systems, with a focus on its potential to revolutionize compute-intensive healthcare tasks such as drug discovery, personalized medicine, DNA sequencing, medical imaging, and operational optimization. Through a comprehensive analysis of existing literature, we have developed taxonomies across different dimensions, including background and enabling technologies, applications, requirements, architectures, security, open issues, and future research directions, providing a panoramic view of the quantum computing paradigm for healthcare. Our survey aims to aid both new and experienced researchers in quantum computing and healthcare by helping them understand the current research landscape, identifying potential opportunities and challenges, and making informed decisions when designing new architectures and applications for quantum computing in healthcare.

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Padalko, Mikhail Alexandrovich, Yuriy Andreevich Shevchenko, Vitalii Yurievich Kapitan, and Konstantin Valentinovich Nefedev. "Parallel Computing of Edwards—Anderson Model." Algorithms 15, no. 1 (December 27, 2021): 13. http://dx.doi.org/10.3390/a15010013.

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A scheme for parallel computation of the two-dimensional Edwards—Anderson model based on the transfer matrix approach is proposed. Free boundary conditions are considered. The method may find application in calculations related to spin glasses and in quantum simulators. Performance data are given. The scheme of parallelisation for various numbers of threads is tested. Application to a quantum computer simulator is considered in detail. In particular, a parallelisation scheme of work of quantum computer simulator.

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Desaki, Yoshihisa. "Quantum Computing." Journal of The Institute of Image Information and Television Engineers 70, no. 7 (2016): 632–36. http://dx.doi.org/10.3169/itej.70.632.

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Mills, Daniel, Seyon Sivarajah, Travis L. Scholten, and Ross Duncan. "Application-Motivated, Holistic Benchmarking of a Full Quantum Computing Stack." Quantum 5 (March 22, 2021): 415. http://dx.doi.org/10.22331/q-2021-03-22-415.

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Quantum computing systems need to be benchmarked in terms of practical tasks they would be expected to do. Here, we propose 3 "application-motivated" circuit classes for benchmarking: deep (relevant for state preparation in the variational quantum eigensolver algorithm), shallow (inspired by IQP-type circuits that might be useful for near-term quantum machine learning), and square (inspired by the quantum volume benchmark). We quantify the performance of a quantum computing system in running circuits from these classes using several figures of merit, all of which require exponential classical computing resources and a polynomial number of classical samples (bitstrings) from the system. We study how performance varies with the compilation strategy used and the device on which the circuit is run. Using systems made available by IBM Quantum, we examine their performance, showing that noise-aware compilation strategies may be beneficial, and that device connectivity and noise levels play a crucial role in the performance of the system according to our benchmarks.

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Hasler, Jennifer, and Eric Black. "Physical Computing: Unifying Real Number Computation to Enable Energy Efficient Computing." Journal of Low Power Electronics and Applications 11, no. 2 (March 26, 2021): 14. http://dx.doi.org/10.3390/jlpea11020014.

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Physical computing unifies real value computing including analog, neuromorphic, optical, and quantum computing. Many real-valued techniques show improvements in energy efficiency, enable smaller area per computation, and potentially improve algorithm scaling. These physical computing techniques suffer from not having a strong computational theory to guide application development in contrast to digital computation’s deep theoretical grounding in application development. We consider the possibility of a real-valued Turing machine model, the potential computational and algorithmic opportunities of these techniques, the implications for implementation applications, and the computational complexity space arising from this model. These techniques have shown promise in increasing energy efficiency, enabling smaller area per computation, and potentially improving algorithm scaling.

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Kendon, Vivien M., Kae Nemoto, and William J. Munro. "Quantum analogue computing." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1924 (August 13, 2010): 3609–20. http://dx.doi.org/10.1098/rsta.2010.0017.

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We briefly review what a quantum computer is, what it promises to do for us and why it is so hard to build one. Among the first applications anticipated to bear fruit is the quantum simulation of quantum systems. While most quantum computation is an extension of classical digital computation, quantum simulation differs fundamentally in how the data are encoded in the quantum computer. To perform a quantum simulation, the Hilbert space of the system to be simulated is mapped directly onto the Hilbert space of the (logical) qubits in the quantum computer. This type of direct correspondence is how data are encoded in a classical analogue computer. There is no binary encoding, and increasing precision becomes exponentially costly: an extra bit of precision doubles the size of the computer. This has important consequences for both the precision and error-correction requirements of quantum simulation, and significant open questions remain about its practicality. It also means that the quantum version of analogue computers, continuous-variable quantum computers, becomes an equally efficient architecture for quantum simulation. Lessons from past use of classical analogue computers can help us to build better quantum simulators in future.

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Wen, Xiao-Jun, Yong-Zhi Chen, Xin-Can Fan, Zheng-Zhong Yi, Zoe L. Jiang, and Jun-Bin Fang. "Quantum blockchain system." Modern Physics Letters B 35, no. 20 (June 4, 2021): 2150343. http://dx.doi.org/10.1142/s0217984921503437.

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Blockchain technology represented by Bitcoin and Ethereum has been deeply developed and widely used due to its broad application prospects such as digital currency and IoT. However, the security of the existing blockchain technologies built on the classical cryptography depends on the computational complexity problem. With the enhancement of the attackers’ computing power, especially the upcoming quantum computers, this kind of security is seriously threatened. Based on quantum hash, quantum SWAP test and quantum teleportation, a quantum blockchain system is proposed with quantum secure communication. In classical cryptographic theory sense, the security of this system is unconditional since it has nothing to do with the attackers’ computing power and computing resources.

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Gopsill, James, Guy Johns, and Ben Hicks. "QUANTUM COMBINATORIAL DESIGN." Proceedings of the Design Society 1 (July 27, 2021): 2511–20. http://dx.doi.org/10.1017/pds.2021.512.

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AbstractCombinatorial Design such as configuration design, design optioneering, component selection, and generative design, is common across engineering. Generating solutions for a combinatorial design task often involves the application of classical computing solvers that can either map or navigate design spaces. However, it has been observed that classical computing resource power-law scales with many design space models. This observation suggests classical computing may not be capable of modelling our future design space needs.To meet future design space modelling needs, this paper examines quantum computing and the characteristics that enables its resources to scale polynomially with design space size. The paper then continues to present a combinatorial design problem that is subsequently represented, constrained and solved by quantum computing. The results of which are the derivation of an initial set of circuits that represent design space constraints. The study shows the game-changing possibilities of quantum computing as an engineering design tool and is the start of an exciting new journey for design research.

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Balakumar, Arvind. "Quantum K-means Clustering and Classical k Means Clustering For Chest Pain Classification Using Qiskit." International Journal for Research in Applied Science and Engineering Technology 10, no. 11 (November 30, 2022): 945–48. http://dx.doi.org/10.22214/ijraset.2022.47484.

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Abstract: Quantum computing is an upcoming field of technology which has a broad scope of increasing the current technology in a robust manner. The application area Quantum computing is very huge which ranges from battery research, protein structure research to advance computing and security areas like cryptography, quantum internet, quantum machine learning and quantum cyber security. The quantum machine learning area seems to be the most interesting because of the computing capability of a real time quantum computer. With the quantum machine learning algorithm, classical algorithm, processing speed of current quantum computers and available data in modern world we could gain insights and find patterns which were previously not possible at all.

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Wei, Shijie, Hang Li, and GuiLu Long. "A Full Quantum Eigensolver for Quantum Chemistry Simulations." Research 2020 (March 23, 2020): 1–11. http://dx.doi.org/10.34133/2020/1486935.

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Quantum simulation of quantum chemistry is one of the most compelling applications of quantum computing. It is of particular importance in areas ranging from materials science, biochemistry, and condensed matter physics. Here, we propose a full quantum eigensolver (FQE) algorithm to calculate the molecular ground energies and electronic structures using quantum gradient descent. Compared to existing classical-quantum hybrid methods such as variational quantum eigensolver (VQE), our method removes the classical optimizer and performs all the calculations on a quantum computer with faster convergence. The gradient descent iteration depth has a favorable complexity that is logarithmically dependent on the system size and inverse of the precision. Moreover, the FQE can be further simplified by exploiting a perturbation theory for the calculations of intermediate matrix elements and obtaining results with a precision that satisfies the requirement of chemistry application. The full quantum eigensolver can be implemented on a near-term quantum computer. With the rapid development of quantum computing hardware, the FQE provides an efficient and powerful tool to solve quantum chemistry problems.

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Thomas Jayachandran, Aurthur Vimalachandran. "Application Overview of Quantum Computing for Gas Turbine Design and Optimization." AI, Computer Science and Robotics Technology 2022 (August 1, 2022): 1–12. http://dx.doi.org/10.5772/acrt.10.

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Conceptual designs require optimization methods to identify the best fit in the system. The article investigates the application of quantum computation in gas turbine design and simulation problems with current technologies, approaches and potential capabilities. Quantum optimization algorithms and quantum annealers help in predicting overall efficiency and optimizing various operating parameters of the gas turbine. A comparison of both classical and quantum computers has been discussed briefly. The classical model challenges are mitigated with the use of quantum computation. A novel hybrid model for simulating gas turbines has been proposed, which consists of a combination of both physics and machine learning to eliminate few of the critical problems faced. This review elaborates application of quantum computing based machine learning for design and optimization of a gas turbine. The overall states of the gas paths of gas turbines could be analyzed using the quantum computing model in the future.

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Klinck, Jannes. "1.1 Quantum Applications - Blogbeitrag: Practical Quantum Computing." Digitale Welt 5, no. 4 (September 20, 2021): 53–56. http://dx.doi.org/10.1007/s42354-021-0406-9.

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DRAGOMAN, Daniela. "Quantum Computing in Graphene." Annals of the Academy of Romanian Scientists Series on Physics and Chemistry 5, no. 1 (2020): 165–80. http://dx.doi.org/10.56082/annalsarsciphyschem.2020.1.165.

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Quantum computing, based on different principles than classical computing, has raised high expectations regarding the increase of computational speed in nano-sized quantum systems. Therefore, the search for implementations of quantum logic gates in photons, spin states, atom/ion traps or superconducting materials, for example, is a very active research area. Graphene has demonstrated already the possibility of implementing reversible logic gates, therefore becoming a compelling candidate for quantum computing applications. The paper presents several proposals of quantum logic gates implementation in graphene, which could work at room temperature and require only current measurements as readout procedures; examples of such quantum gates are Hadamard, C-NOT, C-phase and Toffoli gates. Besides these gates, it is shown that quantum algorithms, such as the modified Deutsch-Jozsa algorithm, can be implemented also in graphene.

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Hu, Qinglong. "Research on International Competition Situation of Quantum Information Technology Based on Patent." Frontiers in Business, Economics and Management 6, no. 2 (November 23, 2022): 204–11. http://dx.doi.org/10.54097/fbem.v6i2.3029.

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As a new subject combining quantum physics and information technology, quantum information involves many fields, such as quantum superposition and interference, quantum teleportation, quantum key distribution, precision measurement and so on.Based on the patent data collected in patsnap, this paper analyzes the innovation in the field of global quantum information technology.The results show that the papers in the field of quantum information are a comprehensive cluster of quantum computing, quantum communication and quantum measurement; The global quantum information theory has experienced a long period of development.Quantum computing has become a research hotspot from 2010 to 2019, and its advantages have been reflected; The life cycle of quantum computing is in a growing period and is the most perfect; The United States leads the world in quantum computing research, and China is the most mature in quantum communication research; Beijing, Shanghai, Jiangsu and Guangdong are the key provinces of quantum information theory patent application in China, and universities or research institutions are the key patent applicants.

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Madbouly, Magda M., Yasser F. Mokhtar, and Saad M. Darwish. "Quantum Game Application to Recovery Problem in Mobile Database." Symmetry 13, no. 11 (October 20, 2021): 1984. http://dx.doi.org/10.3390/sym13111984.

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Mobile Computing (MC) is a relatively new concept in the world of distributed computing that is rapidly gaining traction. Due to the dynamic nature of mobility and the limited bandwidth available on wireless networks, this new computing environment for mobile devices presents significant challenges in terms of fault-tolerant system development. As a consequence, traditional fault-tolerance techniques are inherently inapplicable to these systems. External circumstances often expose mobile systems to failures in communication or data storage. In this article, a quantum game theory-based recovery model is proposed in the case of a mobile host’s failure. Several of the state-of-the-art recovery protocols are selected and analyzed in order to identify the most important variables influencing the recovery mechanism, such as the number of processes, the time needed to send messages, and the number of messages logged-in time. Quantum game theory is then adapted to select the optimal recovery method for the given environment variables using the proposed utility matrix of three players. Game theory is the study of mathematical models of situations in which intelligent rational decision-makers face conflicting interests (alternative recovery procedures). The purpose of this study is to present an adaptive algorithm based on quantum game theory for selecting the most efficient context-aware computing recovery procedure. The transition from a classical to a quantum domain is accomplished in the proposed model by treating strategies as a Hilbert space rather than a discrete set and then allowing for the existence of linear superpositions between classical strategies; this naturally increases the number of possible strategic choices available to each player from a numerable to a continuous set. Numerical data are provided to demonstrate feasibility.

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Baiskhiyar, Divya, and Ravi Kumar. "Quantum Computing-Applications in Bioinformatics." International Journal of Computer Applications 177, no. 12 (October 17, 2019): 26–28. http://dx.doi.org/10.5120/ijca2019919527.

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Kanamori, Yoshito, and Seong-Moo Yoo. "Quantum Computing: Principles and Applications." Journal of International Technology and Information Management 29, no. 2 (January 1, 2020): 43–71. http://dx.doi.org/10.58729/1941-6679.1410.

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Spagnolo, Michele, Joshua Morris, Simone Piacentini, Michael Antesberger, Francesco Massa, Andrea Crespi, Francesco Ceccarelli, Roberto Osellame, and Philip Walther. "Experimental photonic quantum memristor." Nature Photonics 16, no. 4 (March 24, 2022): 318–23. http://dx.doi.org/10.1038/s41566-022-00973-5.

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AbstractMemristive devices are a class of physical systems with history-dependent dynamics characterized by signature hysteresis loops in their input–output relations. In the past few decades, memristive devices have attracted enormous interest in electronics. This is because memristive dynamics is very pervasive in nanoscale devices, and has potentially groundbreaking applications ranging from energy-efficient memories to physical neural networks and neuromorphic computing platforms. Recently, the concept of a quantum memristor was introduced by a few proposals, all of which face limited technological practicality. Here we propose and experimentally demonstrate a novel quantum-optical memristor (based on integrated photonics) that acts on single-photon states. We fully characterize the memristive dynamics of our device and tomographically reconstruct its quantum output state. Finally, we propose a possible application of our device in the framework of quantum machine learning through a scheme of quantum reservoir computing, which we apply to classical and quantum learning tasks. Our simulations show promising results, and may break new ground towards the use of quantum memristors in quantum neuromorphic architectures.

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Tchórzewski, Jerzy, Dariusz Ruciński, and Przemysław Domański. "Artificial neural network inspired by quantum computing solutions using the movement model of the PR-02 robot." ITM Web of Conferences 19 (2018): 01007. http://dx.doi.org/10.1051/itmconf/20181901007.

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The paper proposes a new method of quantum computing using control and systems theory as well as matrix-quantum computing. The algorithm developed on the basis of the PR-02 robot’s arm’s movement was implemented in using the Neural Network Toolbox. The application of the neural model instead of the analytic model allowed for obtaining the improvement of the trajectory of the PR-02 robot’s arm movement, while the application of the quantum artificial neural network for the assumed number of quasi-parallel computations equal 1000 did not result in the improvement of the model.

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Schäfermeier, Clemens. "1. Quantum Applications - Fachbeitrag: Quantum computing comfort zones." Digitale Welt 5, no. 4 (September 20, 2021): 21–23. http://dx.doi.org/10.1007/s42354-021-0399-4.

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Habibi, Mohammad Reza, Saeed Golestan, Ali Soltanmanesh, Josep M. Guerrero, and Juan C. Vasquez. "Power and Energy Applications Based on Quantum Computing: The Possible Potentials of Grover’s Algorithm." Electronics 11, no. 18 (September 15, 2022): 2919. http://dx.doi.org/10.3390/electronics11182919.

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In quantum computing, calculations are achieved using quantum mechanics. Typically, two main phenomena of quantum mechanics (i.e., superposition and entanglement) allow quantum computing to solve some problems more efficiently than classical algorithms. The most well-known advantage of quantum computing is the speedup of some of the calculations, which have been performed before by classical applications. Scientists and engineers are attempting to use quantum computing in different fields of science, e.g., drug discovery, chemistry, computer science, etc. However, there are few attempts to use quantum computing in power and energy applications. This paper tries to highlight this gap by discussing one of the most famous quantum computing algorithms (i.e., Grover’s algorithm) and discussing the potential applications of this algorithm in power and energy systems, which can serve as one of the starting points for using Grover’s algorithm in power and energy systems.

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Ukwuoma, Henry Chima, Gabriel Arome, Aderonke Thompson, and Boniface Kayode Alese. "Post-quantum cryptography-driven security framework for cloud computing." Open Computer Science 12, no. 1 (January 1, 2022): 142–53. http://dx.doi.org/10.1515/comp-2022-0235.

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Abstract Data security in the cloud has been a major issue since the inception and adoption of cloud computing. Various frameworks have been proposed, and yet data breach prevails. With encryption being the dominant method of cloud data security, the advent of quantum computing implies an urgent need to proffer a model that will provide adequate data security for both classical and quantum computing. Thus, most cryptosystems will be rendered susceptible and obsolete, though some cryptosystems will stand the test of quantum computing. The article proposes a model that comprises the application of a variant of McEliece cryptosystem, which has been tipped to replace Rivest–Shamir–Adleman (RSA) in the quantum computing era to secure access control data and the application of a variant of N-th degree truncated polynomial ring units (NTRU) cryptosystem to secure cloud user data. The simulation of the proposed McEliece algorithm showed that the algorithm has a better time complexity than the existing McEliece cryptosystem. Furthermore, the novel tweaking of parameters S and P further improves the security of the proposed algorithms. More so, the simulation of the proposed NTRU algorithm revealed that the existing NTRU cryptosystem had a superior time complexity when juxtaposed with the proposed NTRU cryptosystem.

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Chen, Jian Cheng, and Ang Yan Tu. "Imploved Real Quantum Evolutionary Algorithm and Application." Applied Mechanics and Materials 241-244 (December 2012): 1710–14. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.1710.

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This paper proposes an improved evolutionary computing method called an improved real quantum evolutionary algorithm (IRQEA) based on analysing the traditional quantum evolutionary algorithm. Quantum chromosomes are divided into real components andprobability amplitude components in IRQEA. One real component shows one candidate real solution obtained the optimal solution by gauss variation. Probability amplitude components maintain the population diversity through trigonometric function changes and realize more candidate solutions by less chromosomes, so as to achieve the algorithm’s better optimization abilities. Through the simulation experiments of seven common functions obtaining the optimal values ,it shows that IRQEA have many good characteristics,such as fast convergence rate and best performance.

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Furrer, Frank J. "Quantum Computing for Everyone." Informatik Spektrum 42, no. 5 (October 2019): 372–74. http://dx.doi.org/10.1007/s00287-019-01229-3.

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Joseph, I., Y. Shi, M. D. Porter, A. R. Castelli, V. I. Geyko, F. R. Graziani, S. B. Libby, and J. L. DuBois. "Quantum computing for fusion energy science applications." Physics of Plasmas 30, no. 1 (January 2023): 010501. http://dx.doi.org/10.1063/5.0123765.

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This is a review of recent research exploring and extending present-day quantum computing capabilities for fusion energy science applications. We begin with a brief tutorial on both ideal and open quantum dynamics, universal quantum computation, and quantum algorithms. Then, we explore the topic of using quantum computers to simulate both linear and nonlinear dynamics in greater detail. Because quantum computers can only efficiently perform linear operations on the quantum state, it is challenging to perform nonlinear operations that are generically required to describe the nonlinear differential equations of interest. In this work, we extend previous results on embedding nonlinear systems within linear systems by explicitly deriving the connection between the Koopman evolution operator, the Perron–Frobenius evolution operator, and the Koopman–von Neumann evolution (KvN) operator. We also explicitly derive the connection between the Koopman and Carleman approaches to embedding. Extension of the KvN framework to the complex-analytic setting relevant to Carleman embedding, and the proof that different choices of complex analytic reproducing kernel Hilbert spaces depend on the choice of Hilbert space metric are covered in the appendixes. Finally, we conclude with a review of recent quantum hardware implementations of algorithms on present-day quantum hardware platforms that may one day be accelerated through Hamiltonian simulation. We discuss the simulation of toy models of wave–particle interactions through the simulation of quantum maps and of wave–wave interactions important in nonlinear plasma dynamics.

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Mahmoudi, Yousra, Nadjet Zioui, Hacène Belbachir, Mohamed Tadjine, and Abdelmounaam Rezgui. "A Brief Review on Mathematical Tools Applicable to Quantum Computing for Modelling and Optimization Problems in Engineering." Emerging Science Journal 7, no. 1 (November 7, 2022): 289–312. http://dx.doi.org/10.28991/esj-2023-07-01-020.

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Since its emergence, quantum computing has enabled a wide spectrum of new possibilities and advantages, including its efficiency in accelerating computational processes exponentially. This has directed much research towards completely novel ways of solving a wide variety of engineering problems, especially through describing quantum versions of many mathematical tools such as Fourier and Laplace transforms, differential equations, systems of linear equations, and optimization techniques, among others. Exploration and development in this direction will revolutionize the world of engineering. In this manuscript, we review the state of the art of these emerging techniques from the perspective of quantum computer development and performance optimization, with a focus on the most common mathematical tools that support engineering applications. This review focuses on the application of these mathematical tools to quantum computer development and performance improvement/optimization. It also identifies the challenges and limitations related to the exploitation of quantum computing and outlines the main opportunities for future contributions. This review aims at offering a valuable reference for researchers in fields of engineering that are likely to turn to quantum computing for solutions. Doi: 10.28991/ESJ-2023-07-01-020 Full Text: PDF

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Heurtel, Nicolas, Andreas Fyrillas, Grégoire de Gliniasty, Raphaël Le Bihan, Sébastien Malherbe, Marceau Pailhas, Eric Bertasi, et al. "Perceval: A Software Platform for Discrete Variable Photonic Quantum Computing." Quantum 7 (February 21, 2023): 931. http://dx.doi.org/10.22331/q-2023-02-21-931.

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We introduce Perceval, an open-source software platform for simulating and interfacing with discrete-variable photonic quantum computers, and describe its main features and components. Its Python front-end allows photonic circuits to be composed from basic photonic building blocks like photon sources, beam splitters, phase-shifters and detectors. A variety of computational back-ends are available and optimised for different use-cases. These use state-of-the-art simulation techniques covering both weak simulation, or sampling, and strong simulation. We give examples of Perceval in action by reproducing a variety of photonic experiments and simulating photonic implementations of a range of quantum algorithms, from Grover's and Shor's to examples of quantum machine learning. Perceval is intended to be a useful toolkit for experimentalists wishing to easily model, design, simulate, or optimise a discrete-variable photonic experiment, for theoreticians wishing to design algorithms and applications for discrete-variable photonic quantum computing platforms, and for application designers wishing to evaluate algorithms on available state-of-the-art photonic quantum computers.

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Umer, Muhammad Junaid, and Muhammad Imran Sharif. "A Comprehensive Survey on Quantum Machine Learning and Possible Applications." International Journal of E-Health and Medical Communications 13, no. 5 (October 31, 2022): 1–17. http://dx.doi.org/10.4018/ijehmc.315730.

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Machine learning is a branch of artificial intelligence that is being used at a large scale to solve science, engineering, and medical tasks. Quantum computing is an emerging technology that has a very high computational ability to solve complex problems. Classical machine learning with traditional systems has some limitations for problem-solving due to a large amount of data availability. Quantum machine learning has high performance and computational ability that can effectively be used to solve computation tasks. This study reviews the latest articles in quantum computing and quantum machine learning. Building blocks of quantum computing and different flavors of quantum algorithms are also discussed. The latest work in quantum neural networks is also presented. In the end, different possible applications of quantum computing are also discussed.

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SZELECZKI, Szilveszter. "Thoughts on the application of quantum-based artificial intelligence for military purposes." Vojenské reflexie 16, no. 3 (2021): 54–70. http://dx.doi.org/10.52651/vr.a.2021.3.54-70.

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In today's information-based society, computer technology is developing rapidly, and thus the speed of operations is increasing exponentially. Fast and dynamic information processing has become one of the basic needs of countries and their organizations. Furthermore, higher levels of info-communication technologies can also be detected. In the field of computing, quantum computers are becoming more and more popular, and their current development process is particularly intense, which in turn has triggered a kind of competition between the countries interested in the subject. The estimated future usability of quantum computers for humans is currently being outlined. Regarding to the new computing capabilities, quantum informatics is closely related to artificial intelligence and military forces can gain unprecedented information superiority through the development.

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Pathak, Nirupma, Santosh Kumar, Neeraj Kumar Misra, and Bandan Kumar Bhoi. "A modular approach for testable conservative reversible multiplexer circuit for nano-electronic confine application." International Nano Letters 9, no. 4 (October 11, 2019): 299–309. http://dx.doi.org/10.1007/s40089-019-00283-9.

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Abstract Quantum technology has an attractive application nowadays for its minimizing the energy dissipation, which is a prominent part of any system-level design. In this article, the significant module of a multiplexer, an extended to n:1 is framed with prominent application in the control unit of the processor. The proposed multiplexer modules are framed by the algorithm, which is extended perspective based. Further, quantum cost and gate count are less to ensure the efficient quantum computing framed. In addition, the QCA computing framework is an attempt to synthesize the optimal primitives in conservative reversible multiplexer in nano-electronic confine application. The developed lemmas is framed to prove the optimal parameters in the reversible circuit. Compared with existing state-of-art-works, the proposed modular multiplexer, the gate count, quantum cost and unit delay are optimal.

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Feng, Y., R. Duan, and M. Ying. "Locally undetermined states, generalized Schmidt decomposition, and application in distributed computing." Quantum Information and Computation 9, no. 11&12 (November 2009): 997–1012. http://dx.doi.org/10.26421/qic9.11-12-5.

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Multipartite quantum states that cannot be uniquely determined by their reduced states of all proper subsets of the parties exhibit some inherit `high-order' correlation. This paper elaborates this issue by giving necessary and sufficient conditions for a pure multipartite state to be locally undetermined, and moreover, characterizing precisely all the pure states sharing the same set of reduced states with it. Interestingly, local determinability of pure states is closely related to a generalized notion of Schmidt decomposition. Furthermore, we find that locally undetermined states have some applications to the well-known consensus problem in distributed computing. To be specific, given some physically separated agents, when communication between them, either classical or quantum, is unreliable, then there exists a totally correct and completely fault-tolerant protocol for them to reach a consensus if and only if they share a priori a locally undetermined quantum state.

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Karafyllidis, Ioannis G., Georgios Ch Sirakoulis, and Panagiotis Dimitrakis. "Memristive Quantum Computing Simulator." IEEE Transactions on Nanotechnology 18 (2019): 1015–22. http://dx.doi.org/10.1109/tnano.2019.2941763.

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Zeng, Yi, Hao Wang, Jin He, Qijun Huang, and Sheng Chang. "A Multi-Classification Hybrid Quantum Neural Network Using an All-Qubit Multi-Observable Measurement Strategy." Entropy 24, no. 3 (March 11, 2022): 394. http://dx.doi.org/10.3390/e24030394.

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Quantum machine learning is a promising application of quantum computing for data classification. However, most of the previous research focused on binary classification, and there are few studies on multi-classification. The major challenge comes from the limitations of near-term quantum devices on the number of qubits and the size of quantum circuits. In this paper, we propose a hybrid quantum neural network to implement multi-classification of a real-world dataset. We use an average pooling downsampling strategy to reduce the dimensionality of samples, and we design a ladder-like parameterized quantum circuit to disentangle the input states. Besides this, we adopt an all-qubit multi-observable measurement strategy to capture sufficient hidden information from the quantum system. The experimental results show that our algorithm outperforms the classical neural network and performs especially well on different multi-class datasets, which provides some enlightenment for the application of quantum computing to real-world data on near-term quantum processors.

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Duan, Hongyu. "The Principles, Algorithms and State-of-Art Applications of Quantum Computing." Journal of Physics: Conference Series 2386, no. 1 (December 1, 2022): 012025. http://dx.doi.org/10.1088/1742-6596/2386/1/012025.

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Abstract Contemporarily, quantum computing has become a popular topic, which is a new approach that is different from classic computing. To be specific, it can deal with information by using mathematical modeling that used to represent quantum mechanics, including superposition, interference, and entanglement. In quantum Computing, information is storage in ‘qubit’, whereas classic computer use bit to store information. This article aims to introduce the principles and some algorithms of quantum computing, and then discuss some up-to-date important development. There are two important algorithms are mentioned in this article, Grover’s algorithms and Shor’s algorithms. According to the analysis, Grover’s algorithms is potentially faster than classic algorithms. However, it requires millions of qubits to make it. Besides, Shor’s algorithms have challenged classic encryption (RSA encryption). Two quantum computer Google Sycamore and Jiuzhang are also mentioned here. The interesting thing is, for some specific question, Jiuzhang performed better than classic computers. Finally, it is found out that the quantum computing is generally slower that classic computer now, due to the restriction of qubit numbers. However, quantum computing still has an advantage in some specific question. These results shed light on guiding further exploration of quantum computer designing.

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Jung, Jihye, and In-Chan Choi. "A multi-commodity network model for optimal quantum reversible circuit synthesis." PLOS ONE 16, no. 6 (June 22, 2021): e0253140. http://dx.doi.org/10.1371/journal.pone.0253140.

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Quantum computing is a newly emerging computing environment that has recently attracted intense research interest in improving the output fidelity, fully utilizing its high computing power from both hardware and software perspectives. In particular, several attempts have been made to reduce the errors in quantum computing algorithms through the efficient synthesis of quantum circuits. In this study, we present an application of an optimization model for synthesizing quantum circuits with minimum implementation costs to lower the error rates by forming a simpler circuit. Our model has a unique structure that combines the arc-subset selection problem with a conventional multi-commodity network flow model. The model targets the circuit synthesis with multiple control Toffoli gates to implement Boolean reversible functions that are often used as a key component in many quantum algorithms. Compared to previous studies, the proposed model has a unifying yet straightforward structure for exploiting the operational characteristics of quantum gates. Our computational experiment shows the potential of the proposed model, obtaining quantum circuits with significantly lower quantum costs compared to prior studies. The proposed model is also applicable to various other fields where reversible logic is utilized, such as low-power computing, fault-tolerant designs, and DNA computing. In addition, our model can be applied to network-based problems, such as logistics distribution and time-stage network problems.

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Guan, Ji, Qisheng Wang, and Mingsheng Ying. "An HHL-based algorithm for computing hitting probabilities of quantum walks." Quantum Information and Computation 21, no. 5&6 (May 2021): 395–404. http://dx.doi.org/10.26421/qic21.5-6-4.

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We present a novel application of the HHL (Harrow-Hassidim-Lloyd) algorithm --- a quantum algorithm solving systems of linear equations --- in solving an open problem about quantum walks, namely computing hitting (or absorption) probabilities of a general (not only Hadamard) one-dimensional quantum walks with two absorbing boundaries. This is achieved by a simple observation that the problem of computing hitting probabilities of quantum walks can be reduced to inverting a matrix. Then a quantum algorithm with the HHL algorithm as a subroutine is developed for solving the problem, which is faster than the known classical algorithms by numerical experiments.

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Qiao, Bi, and H. E. Ruda. "Green functions for nonlinear operators and application to quantum computing." Physica A: Statistical Mechanics and its Applications 334, no. 3-4 (March 2004): 459–76. http://dx.doi.org/10.1016/j.physa.2003.10.077.

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Li, Kai, Daowen Qiu, Lvzhou Li, Shenggen Zheng, and Zhenbang Rong. "Application of distributed semi-quantum computing model in phase estimation." Information Processing Letters 120 (April 2017): 23–29. http://dx.doi.org/10.1016/j.ipl.2016.12.002.

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Journal articles on the topic 'Application of quantum computing'

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