Quantum Computing (QC) is a rapidly evolving research field that has garnered significant attention due to its potential to revolutionize various domains such as cryptography, optimization, and machine learning. In this article, we conduct an extensive analysis of the evolution of QC research within the realm of High Performance Computing (HPC) over a span of ten years, up to 2023. Through bibliometric analysis and advanced science mapping techniques, we uncover key thematic areas that have emerged in the field, including quantum algorithms, simulation, parallel-computing, deep learning, machine learning, and encryption. This analysis highlights the interdisciplinary nature of QC, which intersects with disciplines such as physics, mathematics, computer science, and materials science. Furthermore, our study elucidates the close relationship between HPC and QC, showcasing how advancements in one field can significantly impact the other. The findings of this study not only provide valuable insights into the past trends and research landscape but also serve as a guide for future research directions, enabling the advancement of knowledge and fostering innovation in computer science. Additionally, our analysis sheds light on the global distribution of research contributions, identifying countries and regions that have made significant strides in QC research, thus presenting potential collaboration opportunities. Overall, this comprehensive study contributes to a deeper understanding of the development of QC within the realm of HPC, offering valuable insights and paving the way for future advancements in this exciting field.
Quantum Computing (QC) is a rapidly evolving research field that has garnered significant attention due to its potential to revolutionize various domains such as cryptography, optimization, and machine learning. In this article, we conduct an extensive analysis of the evolution of QC research within the realm of High Performance Computing (HPC) over a span of ten years, up to 2023. Through bibliometric analysis and advanced science mapping techniques, we uncover key thematic areas that have emerged in the field, including quantum algorithms, simulation, parallel-computing, deep learning, machine learning, and encryption. This analysis highlights the interdisciplinary nature of QC, which intersects with disciplines such as physics, mathematics, computer science, and materials science. Furthermore, our study elucidates the close relationship between HPC and QC, showcasing how advancements in one field can significantly impact the other. The findings of this study not only provide valuable insights into the past trends and research landscape but also serve as a guide for future research directions, enabling the advancement of knowledge and fostering innovation in computer science. Additionally, our analysis sheds light on the global distribution of research contributions, identifying countries and regions that have made significant strides in QC research, thus presenting potential collaboration opportunities. Overall, this comprehensive study contributes to a deeper understanding of the development of QC within the realm of HPC, offering valuable insights and paving the way for future advancements in this exciting field.
Quantum computing (QC) has the potential to be the next abstruse technology, with a wide range of possible applications and ramifications for organizations and markets. QC provides an exponential speedup by employing quantum mechanics principles, including superposition and entanglement. The potential advantages offered by the revolutionary paradigm have propelled scientific productions. Therefore, a highly pertinent investigation is required to elucidate the evolution of path-breaking trajectories for scientific advances. This study confronts the idea by presenting a scientometric analysis for the recent decade of literature collected from the Web of Science database in the computer science discipline. The scientometric implications of the article identify the significant research domains and provide an intensive insight into the publication patterns, country collaboration, geographical analysis, citation patterns, eminent journals, and research frontiers of each domain of QC. The scholarly literature analysis identifies key challenges in the QC knowledge domain. Overall, the inference reveals an evolutionary pathway for future research directives and collaboration in the domains of QC research. The research findings provide innovative significance to information scientists by presenting a comprehensive overview of QC research to help them find relevant applications, research topics, and key challenges.
Quantum computing (QC) has emerged as a promising research area transitioning from theory to practical realization, driven by interdisciplinary integration. To gain a comprehensive understanding of the evolving research landscape in QC, this study conducts a scientometric analysis of scientific literature retrieved from the Scopus database between 2010 and 2023. Employing the CiteSpace visualization tool, this study examines publication trends, citation patterns, and identifies the prestigious journals in literature. Furthermore, collaboration analysis reveals the top collaborating countries highlighting the active global network of research in QC. Moreover, author cocitation analysis identifies prominent contributors, underscoring their impact and influence in the field. In addition, keyword cooccurrence analysis and thematic analysis pinpoints the areas of significant interest and emerging research frontiers. The content analysis further explores these findings to provide in-depth insights in to themes and trends shaping the field. By providing insights into the evolution of QC, this study contributes to a deeper understanding of technological advancements and determines the future pathway of the field.
Abstract Quantum computing has rapidly emerged as one of the fastest-growing research domains, driven by both technological breakthroughs and the promise of computational advantages over classical systems. This study presents a comprehensive bibliometric analysis of the global quantum computing literature from 1980 to 2025, comprising 31,662 publications indexed in Scopus and accumulating over 800,000 citations. Using advanced bibliometric techniques—including co-authorship mapping, keyword co-occurrence networks, co-citation analysis, and centrality measures—we characterize publication trends, institutional contributions, collaborative structures, and thematic evolution across the field. The results reveal exponential growth in output since 2015, led primarily by the United States, China, and Europe, with key institutions such as MIT, the Chinese Academy of Sciences, CNRS, and the University of Waterloo at the forefront. The intellectual structure exhibits a dual-core configuration, with foundational algorithmic work (e.g. Shor, Grover, Nielsen & Chuang) tightly connected to emerging NISQ-era applications such as quantum machine learning, cryptography, and hybrid algorithms. Keyword analysis reveals the progressive expansion from core quantum algorithms toward increasingly diverse applied domains in healthcare, finance, chemistry, energy, and climate modeling. Public funding bodies (e.g. NSFC, NSF, European Commission, DOE, DoD, MoST) and private-sector investment from major technology firms are jointly driving this translational acceleration. Together, these findings provide an integrated quantitative map of the field’s evolution, offering valuable insight for future scientific policy, international collaboration, and strategic funding initiatives.
Abstract: This article presents a comprehensive review of the integration of quantum computing with High-Performance Computing (HPC), examining current trends, challenges, and future directions. We explore the fundamental principles of quantum computing and their relevance to HPC, followed by an analysis of state-of-the-art quantum algorithms and hybrid quantum-classical systems. The article addresses key technical challenges in hardware and software integration, as well as scalability and stability issues in quantum-enhanced HPC systems. Through a series of case studies, we demonstrate the practical applications and potential impact of quantum-HPC integration across various industries, including finance, drug discovery, and logistics. Our findings highlight the transformative potential of quantum computing in HPC, suggesting unprecedented improvements in computational speed and efficiency. The article concludes with an overview of emerging quantum technologies and identifies promising research opportunities, emphasizing the importance of collaboration between academia and industry. This work serves as a valuable resource for researchers, engineers, and industry professionals seeking to understand and leverage the synergy between quantum computing and HPC, paving the way for future innovations in computational capabilities
Quantum computing represents a paradigm shift in computational capabilities, promising to solve problems that are intractable for classical computers. This paper explores the architecture, implementation, and operational aspects of quantum computing, focusing on its applications in various fields. I conducted a comprehensive literature review to identify existing research gaps and propose methodologies for effective quantum computing implementation. My findings highlight the potential of quantum computing in optimization, cryptography, and machine learning, among other areas. This research paper provides a comprehensive examination of the architecture, implementation, and operational strategies of quantum computing, with a focus on its diverse applications in optimization, cryptography, and machine learning. Through an extensive literature review, I identify critical research gaps and propose innovative methodologies for effective quantum computing implementation. I conclude with strategic recommendations for future research directions, emphasizing the importance of enhancing quantum hardware, developing hybrid algorithms, and fostering interdisciplinary collaborations. This foundational study not only deepens the understanding of quantum computing’s current state but also paves the way for future advancements in this rapidly evolving field. The insights gained from the literature review, methodology, and results sections contribute to a deeper understanding of the current state of quantum computing and its potential applications.
A revolutionary technology impacting the field of science, engineering, and education is Quantum computing. Quantum Computing in education is a discipline regarding its application to teaching and learning. The focus of the paper is a bibliometric analysis of academic literature on quantum computing in education to identify the intellectual structure thereof, patterns of growth, and future research perspectives. It is based on the Scopus database as a primary source of data. It covers 104 relevant publications published during 2011-2025. They were sorted and analyzed with the help of Bibliometrix package and its Biblioshiny interface in R to show the annual trends of publications. The findings indicate that quantum computing education is becoming of academic interest, and the number of research materials is growing rapidly since 2020. The highly interdisciplinary nature, with engineering, computer science, physics, and social sciences, respectively, playing the dominant role. There is a transition towards more basic quantum concepts into applied educational concepts, such as curriculum development, engineering education, teaching practices, and student learning. The paper has an important implication for researchers, teachers, and policy formulators. It also outlines the direction of future research that can be used to advance the sustainable development of quantum computing education.