Analytical Mapping of Materials Science in Quantum Computing using Cite Space

被引:1
|
作者
Sood, Vaishali [1 ]
Chauhan, R. P. [1 ]
机构
[1] NIT Kurukshetra, Dept Phys, Thanesar 136119, India
关键词
Quantum Mechanics; Qubit; Scientometric Analysis; Quantum Entanglement; Keyword Co-occurrence Analysis; STATE;
D O I
10.56042/ijems.v30i3.3672
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Quantum computing is a rapidly growing technology that exploits conventional information theory, computer science, and quantum mechanics principles to address complicated computational problems. The recent breakthroughs in information and communication technologies have yielded profound and intriguing insights into quantum computing research. For more advances in quantum computing, researchers are currently concentrating on exploiting material science in this burgeoning research domain to achieve outperform processing power. Henceforth, a scientometric analysis is undertaken to extract the role of material science in quantum computing by analyzing the published academic bibliometric data using CiteSpace. It appraises the research status quo of the field by analyzing yearly publication growth rate, average citation structure analysis, international research collaboration analysis, most cited publication analysis, and keyword co-occurrence network analysis. It deduced that two-qubit gates, quantum entanglement, and spin fluctuation are the research hotspots. Superconducting qubits and spin-orbit coupling are the current most active research areas in material science assisted-quantum computing research. China, the United States, and Japan are mediating in this field. Furthermore, it offers future research directives and significant clues to researchers for the further diffusion of knowledge in the research domain.
引用
收藏
页码:460 / 467
页数:8
相关论文
共 50 条
  • [1] Advances and opportunities in materials science for scalable quantum computing
    Vincenzo Lordi
    John M. Nichol
    [J]. MRS Bulletin, 2021, 46 : 589 - 595
  • [2] Advances and opportunities in materials science for scalable quantum computing
    Lordi, Vincenzo
    Nichol, John M.
    [J]. MRS BULLETIN, 2021, 46 (07) : 589 - 595
  • [3] Quantum computing and materials science: A practical guide to applying quantum annealing to the configurational analysis of materials
    Camino, B.
    Buckeridge, J.
    Warburton, P. A.
    Kendon, V.
    Woodley, S. M.
    [J]. JOURNAL OF APPLIED PHYSICS, 2023, 133 (22)
  • [4] Towards quantum state preparation with materials science: An analytical review
    Sood, Vaishali
    Chauhan, Rishi Pal
    [J]. INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY, 2023, 123 (18)
  • [5] Extending the reach of quantum computing for materials science with machine learning potentials
    Schuhmacher, Julian
    Mazzola, Guglielmo
    Tacchino, Francesco
    Dmitriyeva, Olga
    Bui, Tai
    Huang, Shanshan
    Tavernelli, Ivano
    [J]. AIP ADVANCES, 2022, 12 (11)
  • [6] Knowledge Mapping of Corporate Financial Performance Research: A Visual Analysis Using Cite Space and Ucinet
    Xue, Wuzhao
    Li, Hua
    Ali, Rizwan
    Rehman, Ramiz Ur
    [J]. SUSTAINABILITY, 2020, 12 (09)
  • [7] Knowledge Mapping of Personalized Recommendation System Research in China: A Bibliometric Analysis Using Cite Space
    Li, Shu-bai
    Yang, Zhong-hua
    Zhu, Ling
    [J]. EDUCATION EXCELLENCE AND INNOVATION MANAGEMENT: A 2025 VISION TO SUSTAIN ECONOMIC DEVELOPMENT DURING GLOBAL CHALLENGES, 2020, : 10317 - 10328
  • [8] Materials simulations using VASP - a quantum perspective to materials science
    Hafner, J.
    [J]. COMPUTER PHYSICS COMMUNICATIONS, 2007, 177 (1-2) : 6 - 13
  • [9] Quantum computing for data science
    Sanders, Barry C.
    [J]. 20TH INTERNATIONAL WORKSHOP ON ADVANCED COMPUTING AND ANALYSIS TECHNIQUES IN PHYSICS RESEARCH, 2023, 2438
  • [10] ANALYTICAL SCIENCE Aromatics in space
    O'Driscoll, Cath
    [J]. CHEMISTRY & INDUSTRY, 2021, 85 (04) : 17 - 17