| dc.description.abstract | Abstract
Quantum computing research has been positioned as one of the forward-looking technologies. It will drive major changes in various industries: national defense, space, advanced materials, biotechnology and medicine, digital finance, and information technology. This study expects to understand the topic and research networks through the topic analysis and bibliometric network analysis for quantum computing. Data were collected from the Web of Science database from 2000 to 2021. The results showed that the number of documents had grown and doubled from 2016 to 2021. The United States and China were the main contributors to scholarly output. The primary research field was dominated by physics. The topic analysis uses the text mining technique, which has the advantage of fast computation and objective evaluation. The seven topics were identified: quantum phase and system, algorithm and optimization, quantum gate and qubit, spin and interactions, quantum states and measurement, implementations and applications, and problem solutions. Bibliometric network analysis is adopted to understand the articles’ relationship through the perspectives of co-occurrence, co-citation, and bibliographic coupling. Topic and network analysis showed similar topics in quantum states, hardware technologies, and algorithms. Besides, network analysis found the specific topological quantum topic by co-citation and bibliographic coupling. The analysis results of this study can help researchers understand quantum computing development more comprehensively with related important references.
Keywords: Quantum computing, Text mining, Topic analysis, Co-occurrence, Co-citation, Bibliographic coupling | en_US |