4.5 Review

Quantum Computing Review: A Decade of Research

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TEM.2023.3284689

Keywords

CiteSpace; quantum algorithms; quantum machine learning; scientometric analysis; Web of Science (WoS)

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Quantum computing has the potential to revolutionize various fields by leveraging principles of quantum mechanics, providing exponential speedup. This study analyzes the scientific literature in the computer science discipline from the Web of Science database to identify key research domains, publication patterns, collaboration, citation patterns, and research frontiers in quantum computing. The findings offer valuable insights for information scientists to understand the field and identify relevant applications, research topics, and challenges.
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.

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