Guang-Can Guo
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- Quantum Mechanics and Applications 9
- Advanced Fiber Laser Technologies 2
- Gyrotron and Vacuum Electronics Research 1
- Artificial Intelligence top 2%
- Quantum Information and Cryptography 11
- Quantum Computing Algorithms and Architecture 8
- Neural Networks and Reservoir Computing 2
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- Quantum chaos and dynamical systems 2
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- Photonic and Optical Devices 3
- Co-authors
- Kai SunChuan-Feng LiShi-Yao ZhuYaron KedemLev VaidmanRosario Lo FrancoGiuseppe CompagnoErika Andersson
- Cited by
- Atomic and Molecular Physics, and OpticsArtificial IntelligenceStatistical and Nonlinear Physics
In The Last Decade
Guang-Can Guo
16 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 49
- Atomic and Molecular Physics, and Optics 962
- Artificial Intelligence 702
- Statistical and Nonlinear Physics 128
- Acoustics and Ultrasonics 7
- Electronic, Optical and Magnetic Materials 129
Countries citing papers authored by Guang-Can Guo
This map shows the geographic impact of Guang-Can Guo'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 Guang-Can Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guang-Can Guo more than expected).
Fields of papers citing papers by Guang-Can Guo
This network shows the impact of papers produced by Guang-Can Guo. 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 Guang-Can Guo. The network helps show where Guang-Can Guo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Guang-Can Guo, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2022 | 4 | |
| 5 | 2022 | 5 | |
| 6 | 2020 | 33 | |
| 7 | 2018 | 16 | |
| 8 | 2017 | 164 | |
| 9 | 2017 | 95 | |
| 10 | 2016 | 158 | |
| 11 | 2016 | 66 | |
| 12 | 2013 | 176 | |
| 13 | 2013 | 218 | |
| 14 | 2008 | 56 | |
| 15 | 2007 | 30 | |
| 16 | 2006 | 103 | |
| 17 | 2006 | 1 | |
| 18 | 1999 | 9 |
About Guang-Can Guo
Guang-Can Guo is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 18 papers that have together received 1.1k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (11 papers), Quantum Mechanics and Applications (9 papers), Quantum Computing Algorithms and Architecture (8 papers), Photonic and Optical Devices (3 papers), Neural Networks and Reservoir Computing (2 papers), Quantum chaos and dynamical systems (2 papers), Advanced Fiber Laser Technologies (2 papers) and Gyrotron and Vacuum Electronics Research (1 paper). The work is most often cited by research in Atomic and Molecular Physics, and Optics (962 citations), Artificial Intelligence (702 citations) and Statistical and Nonlinear Physics (128 citations). Guang-Can Guo has collaborated with scholars based in China, Germany and Hungary. Frequent co-authors include Kai Sun, Chuan-Feng Li, Shi-Yao Zhu, Yaron Kedem, Lev Vaidman, Rosario Lo Franco, Giuseppe Compagno, Erika Andersson, Xiao Xiong and Cheng Wang. Their work appears in journals such as Physical Review Letters, Nature Communications, Physical Review A, New Journal of Physics and Physics Letters A.
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.