Exploring the Role of Material Science in Advancing Quantum Machine Learning: A Scientometric Study

Mathematics, Journal Year: 2025, Volume and Issue: 13(6), P. 958 - 958

Published: March 14, 2025

Quantum Machine Learning (QML) opens up exciting possibilities for tackling problems that are incredibly complex and consume a lot of time. The drive to make QML reality has sparked significant progress in material science, inspiring growing number research publications the field. In this study, we extracted articles from Scopus database understand contribution science advancement QML. This scientometric analysis accumulated 1926 published over 11 years spanning 2014 2024. A total 55 countries contributed domain QML, among which top 10 65.7% out publications; USA is on top, with 19.47% globally. 57 authors area different countries. From 2024, had an average citation impact 32.12 citations per paper; year 2015 received 16.7% citations, highest years, paper, 61.4% total. study also identifies most document 2017, source title Journal Physics Condensed Matter, having count 2649 normalized index (NCII) 91.34.

Language: Английский

Physics informed quantum computing: A decade scientometric analysis

Journal of Computational Science, Journal Year: 2024, Volume and Issue: 81, P. 102382 - 102382

Published: July 8, 2024

Language: Английский