Xiang-Jun Ye
Impact in
- Artificial Intelligence top 5%
- Quantum Information and Cryptography
- Quantum Computing Algorithms and Architecture
- Neural Networks and Reservoir Computing
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- Quantum Mechanics and Applications
- Quantum optics and atomic interactions
- Quantum and electron transport phenomena
- Cold Atom Physics and Bose-Einstein Condensates
- Mechanical and Optical Resonators
Papers in
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- Quantum Mechanics and Applications 10
- Quantum optics and atomic interactions 1
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- Quantum Information and Cryptography 10
- Quantum Computing Algorithms and Architecture 8
- Neural Networks and Applications 1
- Co-authors
- Chuan‐Feng Li (7 shared papers)Guang‐Can Guo (5 shared papers)Chao Zhang (2 shared papers)Changliang Ren (3 shared papers)Xiao‐Min Hu (2 shared papers)Bi‐Heng Liu (2 shared papers)Yun‐Feng Huang (1 shared paper)Cen-Xiao Huang (1 shared paper)
In The Last Decade
Xiang-Jun Ye
10 papers receiving 337 citations
Peers
Comparison fields: 5 of 24
- Artificial Intelligence 319
- Atomic and Molecular Physics, and Optics 296
- Acoustics and Ultrasonics 6
- Statistical and Nonlinear Physics 17
- Computational Theory and Mathematics 8
Countries citing papers authored by Xiang-Jun Ye
This map shows the geographic impact of Xiang-Jun Ye's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiang-Jun Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiang-Jun Ye more than expected).
Fields of papers citing papers by Xiang-Jun Ye
This network shows the impact of papers produced by Xiang-Jun Ye. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiang-Jun Ye. The network helps show where Xiang-Jun Ye may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiang-Jun Ye, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 154 | |
| 2 | 2016 | 34 | |
| 3 | 2020 | 33 | |
| 4 | 2019 | 30 | |
| 5 | 2018 | 26 | |
| 6 | 2019 | 23 | |
| 7 | 2018 | 21 | |
| 8 | 2018 | 18 | |
| 9 | 2017 | 5 | |
| 10 | 2017 | 1 |
About Xiang-Jun Ye
Xiang-Jun Ye is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence, Infectious Diseases, Organic Chemistry and Surgery, having authored 10 papers that have together received 345 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (10 papers), Quantum Mechanics and Applications (10 papers), Quantum Computing Algorithms and Architecture (8 papers), Quantum optics and atomic interactions (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Artificial Intelligence (319 citations), Atomic and Molecular Physics, and Optics (296 citations), Acoustics and Ultrasonics (6 citations), Statistical and Nonlinear Physics (17 citations) and Computational Theory and Mathematics (8 citations). Xiang-Jun Ye has collaborated with scholars based in China, Singapore and Germany. Frequent co-authors include Chuan‐Feng Li, Guang‐Can Guo, Chao Zhang, Changliang Ren, Xiao‐Min Hu, Bi‐Heng Liu, Yun‐Feng Huang, Cen-Xiao Huang, Yu Cai and Yu Guo. Their work appears in journals such as Physical Review Letters, Scientific Reports, Physical review. A and npj Quantum Information.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.