Quantum computing is a vital research field in science and technology. One of the fundamental questions hardly known is how quantum computing research is developing to support scientific advances and the evolution of path-breaking technologies for economic, industrial, and social change. This study confronts the question here by applying methods of computational scientometrics for publication analyses to explain the structure and evolution of quantum computing research and technologies over a 30-year period. Results reveal that the evolution of quantum computing from 1990 to 2020 has a considerable average increase of connectivity in the network (growth of degree centrality measure), a moderate increase of the average influence of nodes on the flow between nodes (little growth of betweenness centrality measure), and a little reduction of the easiest access of each node to all other nodes (closeness centrality measure). This evolutionary dynamics is due to the increase in size and complexity of the network in quantum computing research over time. This study also suggests that the network of quantum computing has a transition from hardware to software research that supports accelerated evolution of technological pathways in quantum image processing, quantum machine learning, and quantum sensors. Theoretical implications of this study show the morphological evolution of the network in quantum computing from a symmetric to an asymmetric shape driven by new inter-related research fields and emerging technological trajectories. Findings here suggest best practices of innovation management based on R&D investments in new technological directions of quantum computing having a high potential for growth and impact in science and markets.
Quantum computing is a vital research field in science and technology. One of the fundamental questions hardly known is how quantum computing research is developing to support scientific advances and the evolution of path-breaking technologies for economic, industrial, and social change. This study confronts the question here by applying methods of computational scientometrics for publication analyses to explain the structure and evolution of quantum computing research and technologies over a 30-year period. Results reveal that the evolution of quantum computing from 1990 to 2020 has a considerable average increase of connectivity in the network (growth of degree centrality measure), a moderate increase of the average influence of nodes on the flow between nodes (little growth of betweenness centrality measure), and a little reduction of the easiest access of each node to all other nodes (closeness centrality measure). This evolutionary dynamics is due to the increase in size and complexity of the network in quantum computing research over time. This study also suggests that the network of quantum computing has a transition from hardware to software research that supports accelerated evolution of technological pathways in quantum image processing, quantum machine learning, and quantum sensors. Theoretical implications of this study show the morphological evolution of the network in quantum computing from a symmetric to an asymmetric shape driven by new inter-related research fields and emerging technological trajectories. Findings here suggest best practices of innovation management based on R&D investments in new technological directions of quantum computing having a high potential for growth and impact in science and markets.
Abstract Quantum computer and computing are areas of theoretical and experimental research having a phase of growth that can generate a tectonic shift of the evolution of technology in society. The scientific and technological development in quantum research is due to a range of driving technological trajectories that are growing to solve more and more complex problems. The goal of this study is to detect emerging research fields and technological trajectories of quantum computing to explain and generalize, whenever possible, the technological characteristics of evolutionary dynamics in science and technology. Database of Scopus concerning documents and patents is used for statistical analyses to determine the growth of research fields and technological trajectories having a high potential impact in science and society. Results suggest that quantum research is driven by emerging scientific and technological trajectories given by Qubits, Quantum optics, Quantum circuit, Semiconductor quantum dots and quantum information. Overall, this study explains, whenever possible, emerging research fields and technological technologies in quantum computing that support scientific and technological change directed to future economic and social progress. Finally, technology analysis of this study can help policymakers to support the allocation of resources for all areas of Quantum Science having a high potential of growth and positive impact in science and society.
This study develops a technology analysis to detect technological trajectories in quantum computing that can lay the foundation of a quantum industry. Study design considers data of 10,089 scientific products in ‘quantum computing’ over 1989–2020 period and 19,266 scientific products in ‘quantum computer’ over 1967–2020 period to cover all scientific production in this research field; a complementary analysis considers 8,505 patents over 1977–2020 in ‘quantum computing’ and 9,792 patents in ‘quantum computer’ over 1985–2020 period. Models of technological evolution applied here show main technological trajectories in quantum computing and computer and their rates of growth that suggest path-breaking directions in quantum technology, such as quantum optics, quantum information, quantum algorithms, quantum entanglement, quantum communication and quantum cryptography. Findings here provide information to extend the knowledge in the evolution of quantum computing and computers to support the management of these new technologies and R&D investments towards innovations generating industrial, economic and social change.
Abstract - Quantum computing has evolved from a physics-driven theoretical concept into a rapidly expanding technological ecosystem encompassing computation, communication, sensing, and security. This paper presents a timeline-based analytical study of this evolution, examining how successive scientific and technological eras shaped the transition from foundational quantum theory to modern noisy intermediate-scale quantum (NISQ) platforms and distributed quantum infrastructures. Rather than offering a purely chronological account, the study evaluates each phase using comparative metrics such as scientific maturity, technological capability, scalability, error resilience, application readiness, and interdisciplinary integration. Beyond technical progress, the paper highlights the growing role of academic institutions in developing foundational methods and workforce capacity, alongside industrial efforts in hardware engineering, cloud-based access, and commercialization. These developments are further reinforced by large-scale public investments through national quantum missions and regional innovation programs, positioning quantum technologies as strategic components of future digital infrastructure. By integrating historical evolution with ecosystem and policy perspectives, this work aims to clarify how scientific constraints, engineering challenges, and institutional drivers collectively shape the current trajectory and future direction of quantum technologies. Key Words: quantum, timeline, global impact, hybrid, evolution
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 is a novel method of computation that uses the principles of quantum mechanics to handle highly challenging situations in a very short amount of time. Quantum technology has the ability to significantly impact worldwide advancement, even prior to the complete deployment of quantum machines. Quantum technology for communication, computation, and sensors has the capacity to revolutionise many industries, and several nations are making investments in this promising field. This includes research investments from both the public and commercial sectors. This article delves into the recent quantum computing advancements and the potential opportunities made possible by quantum technology in the next few decades. We outline a vision and scientific innovation for embracing the quantum age, as well as explore the pioneering applications of quantum computing. We also highlight software tools and platforms for quantum programming to unlock the power of computing and revolutionize the world. Finally, we identify the groundbreaking impacts of quantum computing on next-generation research and discuss the benefits of unleashing its revolutionary capabilities.
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.