Kok Chuan Tan
- Atomic and Molecular Physics, and Optics top 5%
- Artificial Intelligence top 2%
- Statistical and Nonlinear Physics top 10%
- Electrical and Electronic Engineering
- Cognitive Neuroscience
- Co-authors
- Hyunseok JeongHyukjoon KwonTyler VolkoffChae-Yeun ParkTomasz PaterekJ.-P. MaillardMauro PaternostroMarco Piani
- Topics
- Quantum Information and Cryptography (20 papers)Quantum Mechanics and Applications (16 papers)Quantum Computing Algorithms and Architecture (11 papers)
- Cited by
- Atomic and Molecular Physics, and OpticsArtificial IntelligenceStatistical and Nonlinear Physics
- Partner nations
- South KoreaSingaporePoland
In The Last Decade
Kok Chuan Tan
20 papers receiving 579 citations
Peers
Comparison fields: 5 of 33
- Atomic and Molecular Physics, and Optics 552
- Artificial Intelligence 552
- Statistical and Nonlinear Physics 71
- Electrical and Electronic Engineering 19
- Cognitive Neuroscience 6
Countries citing papers authored by Kok Chuan Tan
This map shows the geographic impact of Kok Chuan Tan'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 Kok Chuan Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kok Chuan Tan more than expected).
Fields of papers citing papers by Kok Chuan Tan
This network shows the impact of papers produced by Kok Chuan Tan. 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 Kok Chuan Tan. The network helps show where Kok Chuan Tan may publish in the future.
Co-authorship network of co-authors of Kok Chuan Tan
This figure shows the co-authorship network connecting the top 25 collaborators of Kok Chuan Tan. A scholar is included among the top collaborators of Kok Chuan Tan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kok Chuan Tan. Kok Chuan Tan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 26 | |
| 3 | 4 | |
| 4 | 3 | |
| 5 | 113 | |
| 6 | 8 | |
| 7 | Nonclassicality of Light as a Quantifiable Resource for Quantum Metrology | 0 |
| 8 | 6 | |
| 9 | 32 | |
| 10 | 34 | |
| 11 | 14 | |
| 12 | 55 | |
| 13 | 10 | |
| 14 | 2 | |
| 15 | 9 | |
| 16 | 118 | |
| 17 | 9 | |
| 18 | 117 | |
| 19 | 16 | |
| 20 | 18 |
About Kok Chuan Tan
Kok Chuan Tan is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Statistical and Nonlinear Physics, having authored 21 papers that have together received 603 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (20 papers), Quantum Mechanics and Applications (16 papers) and Quantum Computing Algorithms and Architecture (11 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (552 citations), Artificial Intelligence (552 citations) and Statistical and Nonlinear Physics (71 citations). Kok Chuan Tan has collaborated with scholars based in South Korea, Singapore and Poland. Frequent co-authors include Hyunseok Jeong, Hyukjoon Kwon, Tyler Volkoff, Chae-Yeun Park, Tomasz Paterek, J.-P. Maillard, Mauro Paternostro, Marco Piani, Kavan Modi and Dagomir Kaszlikowski. Their work appears in journals such as Physical Review Letters, Physical Review A and New Journal of Physics.
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.