| 摘要: | 摘要
量子運算研究近年已定位是影響人類未來的前瞻技術之一，量子運算將帶動各項產業重大轉變，無論是國防、太空、先進材料、生技醫藥、數位金融與資訊科技等。本研究期望運用主題分析法了解量子運算研究的主題趨勢發展，以及書目網絡分析法探討研究文獻之間的網絡關係。蒐集從2000年到2021年間Web of Science 的資料庫文獻。結果顯示文獻數量從2016年以後到2021之間增幅超過一倍，美國與中國的發表數量是主要貢獻來源，研究領域以物理類為主。主題分析法對蒐集的文獻進行文字採礦，具有快速處理巨量資料與減少人為判斷的優點，篩選出的七個主題為：量子相位與系統模型、演算法改良與最佳化、量子邏輯閘與量子位元、自旋特性與交互作用、量子態與量測方法、實現與應用、和問題解決方案。書目網絡分析從作者關鍵詞共現字分析、文獻共被引分析與書目耦合的三種計量方式，整理出文獻間彼此脈絡關係，所收斂的集群議題與主題分析可相互參考。主題與網絡分析法在量子物理態、硬體技術和演算法均呈現相同熱門趨勢，但拓樸量子的集群在網絡分析法的結果，無論從共被引分析或書目耦合均出現一個集中卻偏離主集群網絡的現象。運用文字採礦的主題分析法可快速挖掘出文獻間的主題趨勢，搭配書目網絡分析的結果，具有不同分析法的觀點、面向及相對多元的剖析，可呈現過往的研究概況，並提供後續研究人員更聚焦與快速掌握量子運算研究主題的發展方向。
關鍵字: 量子運算、文字採礦、主題分析、共現字分析、共被引分析、書目耦合
;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 |
