Sergey Knysh
Impact in
- Artificial Intelligence top 2%
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Neural Networks and Reservoir Computing
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- Quantum many-body systems
- Quantum Mechanics and Applications
- Quantum and electron transport phenomena
Papers in
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- Quantum Computing Algorithms and Architecture 11
- Quantum Information and Cryptography 8
- Neural Networks and Reservoir Computing 3
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- Quantum many-body systems 3
- Quantum and electron transport phenomena 2
- Co-authors
- Vadim Smelyanskiy (8 shared papers)Gabriel A. Durkin (1 shared paper)A. P. Young (1 shared paper)A. P. Young (2 shared papers)Davide Venturelli (3 shared papers)Rupak Biswas (2 shared papers)Bryan O’Gorman (2 shared papers)Salvatore Mandrà (2 shared papers)
- Journals
- Physical Review Letters (3 papers)Nature Communications (1 paper)Physical Review X (1 paper)Physical Review A (1 paper)Parallel Computing (1 paper)
- Partner nations
- United StatesJapan
In The Last Decade
Sergey Knysh
13 papers receiving 609 citations
Peers
Comparison fields: 5 of 49
- Artificial Intelligence 549
- Atomic and Molecular Physics, and Optics 350
- Acoustics and Ultrasonics 6
- Computational Theory and Mathematics 92
- Condensed Matter Physics 45
Countries citing papers authored by Sergey Knysh
This map shows the geographic impact of Sergey Knysh'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 Sergey Knysh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergey Knysh more than expected).
Fields of papers citing papers by Sergey Knysh
This network shows the impact of papers produced by Sergey Knysh. 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 Sergey Knysh. The network helps show where Sergey Knysh may publish in the future.
Co-authors
The 22 scholars most cited alongside Sergey Knysh, 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 | 2015 | 128 | |
| 2 | 2011 | 124 | |
| 3 | 2010 | 114 | |
| 4 | 2008 | 93 | |
| 5 | 2016 | 57 | |
| 6 | 2016 | 48 | |
| 7 | 2015 | 20 | |
| 8 | 2017 | 17 | |
| 9 | 2004 | 8 | |
| 10 | 2020 | 7 | |
| 11 | 2008 | 5 | |
| 12 | 2020 | 4 | |
| 13 | 2010 | 2 |
About Sergey Knysh
Sergey Knysh is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Condensed Matter Physics, Molecular Biology and Mathematical Physics, having authored 13 papers that have together received 627 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (11 papers), Quantum Information and Cryptography (8 papers), Theoretical and Computational Physics (3 papers), Quantum many-body systems (3 papers), Neural Networks and Reservoir Computing (3 papers), Quantum and electron transport phenomena (2 papers), Cloud Computing and Resource Management (1 paper) and Markov Chains and Monte Carlo Methods (1 paper). The work is most often cited by research in Artificial Intelligence (549 citations), Atomic and Molecular Physics, and Optics (350 citations), Acoustics and Ultrasonics (6 citations), Computational Theory and Mathematics (92 citations) and Condensed Matter Physics (45 citations). Sergey Knysh has collaborated with scholars based in United States and Japan. Frequent co-authors include Vadim Smelyanskiy, Gabriel A. Durkin, A. P. Young, A. P. Young, Davide Venturelli, Rupak Biswas, Bryan O’Gorman, Salvatore Mandrà, Alejandro Perdomo‐Ortiz and Hidetoshi Nishimori. Their work appears in journals such as Physical Review Letters, Nature Communications, Physical Review X, Physical Review A and Parallel Computing.
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.