Kyle Matsuda
Impact in
-
- Cold Atom Physics and Bose-Einstein Condensates
- Atomic and Subatomic Physics Research
- Quantum, superfluid, helium dynamics
- Advanced Frequency and Time Standards
- Quantum optics and atomic interactions
- Strong Light-Matter Interactions
- Spectroscopy top 10%
- Spectroscopy and Laser Applications
Papers in
-
- Cold Atom Physics and Bose-Einstein Condensates 12
- Atomic and Subatomic Physics Research 7
- Quantum, superfluid, helium dynamics 4
- Strong Light-Matter Interactions 2
- Quantum optics and atomic interactions 1
- Quantum and electron transport phenomena 1
-
- Quantum Information and Cryptography 5
- Co-authors
- William G. TobiasJun YeLuigi De MarcoGiacomo ValtolinaLouis BaumIvan KozyryevJohn M. DoyleJun-Ru Li
- Journals
- Science (3 papers)Physical Review Letters (3 papers)ChemPhysChem (1 paper)New Journal of Physics (1 paper)Nature (1 paper)
- Partner nations
- United StatesFranceAustria
In The Last Decade
Kyle Matsuda
12 papers receiving 781 citations
Peers
Comparison fields: 5 of 30
- Atomic and Molecular Physics, and Optics 766
- Spectroscopy 135
- Artificial Intelligence 162
- Condensed Matter Physics 45
- Statistical and Nonlinear Physics 23
Countries citing papers authored by Kyle Matsuda
This map shows the geographic impact of Kyle Matsuda'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 Kyle Matsuda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle Matsuda more than expected).
Fields of papers citing papers by Kyle Matsuda
This network shows the impact of papers produced by Kyle Matsuda. 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 Kyle Matsuda. The network helps show where Kyle Matsuda may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Kyle Matsuda, 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 | 2023 | 52 | |
| 2 | 2022 | 31 | |
| 3 | 2021 | 28 | |
| 4 | 2021 | 71 | |
| 5 | 2020 | 14 | |
| 6 | 2020 | 78 | |
| 7 | 2020 | 21 | |
| 8 | 2019 | 195 | |
| 9 | 2017 | 180 | |
| 10 | 2016 | 24 | |
| 11 | 2016 | 80 | |
| 12 | 2015 | 25 |
About Kyle Matsuda
Kyle Matsuda is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence, Spectroscopy, Infectious Diseases and Organic Chemistry, having authored 12 papers that have together received 799 indexed citations. Recurring topics across this work include Cold Atom Physics and Bose-Einstein Condensates (12 papers), Atomic and Subatomic Physics Research (7 papers), Quantum Information and Cryptography (5 papers), Quantum, superfluid, helium dynamics (4 papers), Strong Light-Matter Interactions (2 papers), Quantum optics and atomic interactions (1 paper), Spectroscopy and Laser Applications (1 paper) and Quantum and electron transport phenomena (1 paper). The work is most often cited by research in Atomic and Molecular Physics, and Optics (766 citations), Spectroscopy (135 citations), Artificial Intelligence (162 citations), Condensed Matter Physics (45 citations) and Statistical and Nonlinear Physics (23 citations). Kyle Matsuda has collaborated with scholars based in United States, France and Austria. Frequent co-authors include William G. Tobias, Jun Ye, Luigi De Marco, Giacomo Valtolina, Louis Baum, Ivan Kozyryev, John M. Doyle, Jun-Ru Li, Jacob P. Covey and Benjamin L. Augenbraun. Their work appears in journals such as Science, Physical Review Letters, ChemPhysChem, New Journal of Physics and Nature.
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.