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.
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.
Quantum computing is a revolutionary field of research in science and technology, which provides sophisticated processing capacity and computation in a finite time frame based on quantum mechanics. It has the great potential to offer more effective and faster solutions to overcome current processing constraints. Therefore, to address the global significance, relevance, and exponential growth, it is imperative to conduct a thorough investigation and promote advancements through rigorous scientometric analysis. The current article presents the knowledge mapping of rapidly expanding quantum computing research using the CiteSpace visualization tool. The foundation of research is the scientific literature on quantum computing extracted from the Scopus database, covering the period of 2008–2022. It provides publication patterns, citation structure, and in-depth keyword co-occurrence network analysis insights to extract emerging research areas. It illustrates a variety of empirical approaches to discover the status quo and evolution. The findings reveal that quantum algorithms serve as the fundamental basis for all research fields, and quantum machine learning is the most active research area nowadays.
Interdisciplinary research has a significant impact on invention. Quantum computing, a cutting-edge emerging technology in this area, has shown remarkable growth and development in the current time. Therefore, an inclusive analysis of the academic literature is needed to understand the research advancement in the domain. The present study fulfills the need by analyzing published academic work from the Scopus database using the CiteSpace visualization tool. The research findings classify the quantum domain into five stages for research exploration, viz. quantum state preparation, quantum entanglement, decoherence, quantum error correction, and quantum optimization. Keyword co-occurrence, document cocitation, and burst analysis of the network pinpoint nascent research topics, inclinations, and advancements in each stage. Inclusively, the systematized and comprehensive study presents an evolutionary pathway for future researchers to gain in-depth knowledge, identify essential research subjects, and identify challenging issues.
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.
Abstract The field of quantum computing has undergone significant expansion and development in recent years. A quantitative and comprehensive examination of the research domain is essential to comprehend research trends and directions in the field. Henceforth, the current paper conducts a scientometric analysis of the academic literature on quantum computing retrieved from the Scopus database to understand the recent advances made by researchers in the domain. The analysis evaluates the state of the discipline's research by examining the most prominent journals and highly referenced articles. CiteSpace is leveraged to visualize the intellectual landscape of quantum state preparation by performing document co‐citation and author co‐citation analysis. The analysis reveals that trapped ions, photonic qubits, superconducting qubits, nitrogen‐vacancy centers, and nuclear spin qubits are the primary research topics in quantum computing. Furthermore, the most current research issues that require attention in the field are measurement‐based qubits, Majorana fermions, and quantum dots.
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.