Quantum computing is the next-generation technology for future human society. This article aims to give a comprehensive and in-depth analysis of the global development status of quantum computing. First, the latest research hotspots of quantum computing are reviewed. Then multiple bibliometric metrics were used to analyse the current development status, research hotspots, technological trends, and the contribution of authors, institutions, and countries in quantum computing from 2016 to 2020. The results confirm that quantum computing is still under development, with the United States and China in the leading position, from where most critical scholars came. The most important institutions are scattered in the United States, China, and France. The characteristics of international cooperation, research impact, topics with the highest Prominence percentile, distinctive keyphrases, and leading source journals within the field were also analysed. The results may provide a quantitative basis for scientific research and decision-making in quantum computing.
Quantum computing is the next-generation technology for future human society. This article aims to give a comprehensive and in-depth analysis of the global development status of quantum computing. First, the latest research hotspots of quantum computing are reviewed. Then multiple bibliometric metrics were used to analyse the current development status, research hotspots, technological trends, and the contribution of authors, institutions, and countries in quantum computing from 2016 to 2020. The results confirm that quantum computing is still under development, with the United States and China in the leading position, from where most critical scholars came. The most important institutions are scattered in the United States, China, and France. The characteristics of international cooperation, research impact, topics with the highest Prominence percentile, distinctive keyphrases, and leading source journals within the field were also analysed. The results may provide a quantitative basis for scientific research and decision-making in quantum computing.
Quantum computing is the next-generation technology for future human society. This article aims to give a comprehensive and in-depth analysis of the global development status of quantum computing. First, the latest research hotspots of quantum computing are reviewed. Then multiple bibliometric metrics were used to analyse the current development status, research hotspots, technological trends, and the contribution of authors, institutions, and countries in quantum computing from 2016 to 2020. The results confirm that quantum computing is still under development, with the United States and China in the leading position, from where most critical scholars came. The most important institutions are scattered in the United States, China, and France. The characteristics of international cooperation, research impact, topics with the highest Prominence percentile, distinctive keyphrases, and leading source journals within the field were also analysed. The results may provide a quantitative basis for scientific research and decision-making in quantum computing.
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.
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.
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.
Purpose: This study explores the improvement in the area of Quantum computing techniques and natural language algorithm, to assist researchers to earn new awareness and detect emerging areas of growth for further research in this field. Methodology: In this study, we apply bibliometric analysis by using R Studio and VOS viewer software, we got our data from the Scopus database after searching via keywords, and before the exclusion, we got 292 papers, then we start to apply the exclusion criteria such as (time limit from 1990 to 2024, Document type: Article, Publication stage: Final, Source type: Journal, and Language: English) then after we applied those criteria we reach to 273 papers. Finding: The results of this study established the development status of the field of Quantum computing techniques and natural language algorithm, we demonstrate the growth rate, and emerging thematic areas for further research, we also identified the most impactful and leading authors, topic trends, keywords, sources, publications, and the relationship between co-authors. These findings assist researchers to guide new research to concentrate on future topic trends. Originality: This study contributes to the literature by identifying the growing interest in Quantum computing techniques and natural language algorithm.
This paper presents a comprehensive systematic and bibliometric review of the rapidly expanding literature on quantum computing. The study addresses six research questions concerning prominent themes, temporal evolution, types of key findings, frequently reported research gaps, higher-order gap typologies, and future research directions. Utilizing a researcher-curated database, the final corpus comprises 153 studies compiled from non-Scopus, Scopus and Web of Science. The results demonstrate that quantum hardware and architecture, algorithms, and theoretical foundations dominate the current literature. Furthermore, publication output has risen significantly between 2018 and 2025. Among the reported findings, algorithmic innovations, performance claims, and hardware advancements are the most common. Despite this progress, the field faces substantial barriers; technical, scalability, fault-tolerance, and methodological-standardization gaps are the most frequently reported. Based on these identified gaps, eight actionable future research directions emerge to guide the scientific community. Ultimately, this review concludes that quantum computing is actively transitioning from a purely physics-driven domain into a multidisciplinary, engineering- and application-oriented science. However, its continued advancement is presently constrained by a hardware-methodology-application triad, wherein reporting practices often outpace empirical verification and standardized benchmarking.