Leo Zhou
Impact in
- Artificial Intelligence top 5%
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Neural Networks and Reservoir Computing
- Stochastic Gradient Optimization Techniques
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- Quantum-Dot Cellular Automata
Papers in
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- Quantum Computing Algorithms and Architecture 7
- Quantum Information and Cryptography 4
- Stochastic Gradient Optimization Techniques 2
- Neural Networks and Reservoir Computing 1
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- Quantum many-body systems 3
- Co-authors
- Edward Farhi (2 shared papers)Sam Gutmann (1 shared paper)Jeffrey Goldstone (1 shared paper)Mikhail D. Lukin (2 shared papers)Soonwon Choi (2 shared papers)Hannes Pichler (1 shared paper)Sheng-Tao Wang (1 shared paper)Chi-Fang Chen (2 shared papers)
- Journals
- Physical review. A (1 paper)Nature Physics (1 paper)Quantum (1 paper)Physical Review C (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- United StatesIsrael
In The Last Decade
Leo Zhou
9 papers receiving 242 citations
Leo Zhou's Hit Papers
Peers
Comparison fields: 5 of 29
- Artificial Intelligence 218
- Computational Theory and Mathematics 72
- Atomic and Molecular Physics, and Optics 84
- Computational Mathematics 1
- Hardware and Architecture 7
Countries citing papers authored by Leo Zhou
This map shows the geographic impact of Leo Zhou'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 Leo Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leo Zhou more than expected).
Fields of papers citing papers by Leo Zhou
This network shows the impact of papers produced by Leo Zhou. 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 Leo Zhou. The network helps show where Leo Zhou may publish in the future.
Co-authors
The 14 scholars most cited alongside Leo Zhou, 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 | The Quantum Approximate Optimization Algorithm and the Sherrington-Kirkpatrick Model at Infinite Size Hit paper breakdown → | 2022 | 132 |
| 2 | 2018 | 33 | |
| 3 | 2014 | 30 | |
| 4 | 2021 | 17 | |
| 5 | 2022 | 16 | |
| 6 | 2025 | 8 | |
| 7 | 2014 | 6 | |
| 8 | 2024 | 6 | |
| 9 | Hamiltonian Sparsification and Gap-Simulation | 2018 | 2 |
About Leo Zhou
Leo Zhou is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Statistical and Nonlinear Physics and Nuclear and High Energy Physics, having authored 9 papers that have together received 250 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (7 papers), Quantum Information and Cryptography (4 papers), Complexity and Algorithms in Graphs (3 papers), Quantum many-body systems (3 papers), Stochastic Gradient Optimization Techniques (2 papers), Advanced Thermodynamics and Statistical Mechanics (1 paper), Particle physics theoretical and experimental studies (1 paper) and Neural Networks and Reservoir Computing (1 paper). The work is most often cited by research in Artificial Intelligence (218 citations), Computational Theory and Mathematics (72 citations), Atomic and Molecular Physics, and Optics (84 citations), Computational Mathematics (1 citation) and Hardware and Architecture (7 citations). Leo Zhou has collaborated with scholars based in United States and Israel. Frequent co-authors include Edward Farhi, Sam Gutmann, Jeffrey Goldstone, Mikhail D. Lukin, Soonwon Choi, Hannes Pichler, Sheng-Tao Wang, Chi-Fang Chen, David Gamarnik and Hsin-Yuan Huang. Their work appears in journals such as Physical review. A, Nature Physics, Quantum, Physical Review C and arXiv (Cornell University).
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.