Sam Pallister
Impact in
- Artificial Intelligence top 5%
- Quantum Computing Algorithms and Architecture
- Quantum Information and Cryptography
- Neural Networks and Reservoir Computing
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- Quantum Mechanics and Applications
- Quantum and electron transport phenomena
- Quantum many-body systems
Papers in
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- Quantum Computing Algorithms and Architecture 4
- Quantum Information and Cryptography 4
- Neural Networks and Reservoir Computing 1
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- Quantum Mechanics and Applications 2
- Orbital Angular Momentum in Optics 1
- Quantum many-body systems 1
- Co-authors
- Ashley Montanaro (2 shared papers)Noah Linden (1 shared paper)Isaac H. Kim (1 shared paper)Ye-Hua Liu (1 shared paper)Eunseok Lee (1 shared paper)N. Meshksar (1 shared paper)David Jennings (1 shared paper)Andrew Sornborger (1 shared paper)
- Journals
- Physical Review Letters (1 paper)Physical Review Research (1 paper)Physical review. A (1 paper)Quantum (1 paper)Bristol Research (University of Bristol) (1 paper)
- Partner nations
- United KingdomPortugalFinland
In The Last Decade
Sam Pallister
5 papers receiving 232 citations
Peers
Comparison fields: 5 of 29
- Artificial Intelligence 226
- Atomic and Molecular Physics, and Optics 130
- Computational Theory and Mathematics 50
- Statistical and Nonlinear Physics 11
- Hardware and Architecture 4
Countries citing papers authored by Sam Pallister
This map shows the geographic impact of Sam Pallister'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 Sam Pallister with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sam Pallister more than expected).
Fields of papers citing papers by Sam Pallister
This network shows the impact of papers produced by Sam Pallister. 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 Sam Pallister. The network helps show where Sam Pallister may publish in the future.
Co-authors
The 13 scholars most cited alongside Sam Pallister, 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 | 2016 | 110 | |
| 2 | 2018 | 72 | |
| 3 | 2022 | 59 | |
| 4 | 2017 | 3 | |
| 5 | 2024 | 1 |
About Sam Pallister
Sam Pallister is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics, Infectious Diseases and Organic Chemistry, having authored 5 papers that have together received 245 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (4 papers), Quantum Information and Cryptography (4 papers), Quantum Mechanics and Applications (2 papers), Numerical Methods and Algorithms (1 paper), Orbital Angular Momentum in Optics (1 paper), Matrix Theory and Algorithms (1 paper), Neural Networks and Reservoir Computing (1 paper) and Quantum many-body systems (1 paper). The work is most often cited by research in Artificial Intelligence (226 citations), Atomic and Molecular Physics, and Optics (130 citations), Computational Theory and Mathematics (50 citations), Statistical and Nonlinear Physics (11 citations) and Hardware and Architecture (4 citations). Sam Pallister has collaborated with scholars based in United Kingdom, Portugal and Finland. Frequent co-authors include Ashley Montanaro, Noah Linden, Isaac H. Kim, Ye-Hua Liu, Eunseok Lee, N. Meshksar, David Jennings, Andrew Sornborger, P. A. Knott and Matteo Lostaglio. Their work appears in journals such as Physical Review Letters, Physical Review Research, Physical review. A, Quantum and Bristol Research (University of Bristol).
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.