Carlos A. Riofrío
- Artificial Intelligence top 5%
- Quantum Information and Cryptography 10
- Quantum Computing Algorithms and Architecture 8
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- Quantum many-body systems 7
- Cold Atom Physics and Bose-Einstein Condensates 6
- Quantum Mechanics and Applications 3
- Atomic and Subatomic Physics Research 2
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- Quantum chaos and dynamical systems 2
- Computational Mechanics top 10%
- Sparse and Compressive Sensing Techniques 3
- Co-authors
- Ivan DeutschPoul JessenB. E. AndersonJens EisertSteven T. FlammiaAaron SmithThomas MonzDaniel Nigg
- Journals
- Physical Review Letters (4 papers)Physical Review A (3 papers)Nature Communications (2 papers)
- Partner nations
- GermanyUnited StatesAustria
In The Last Decade
Carlos A. Riofrío
16 papers receiving 402 citations
Peers
Comparison fields: 5 of 35
- Artificial Intelligence 339
- Atomic and Molecular Physics, and Optics 290
- Acoustics and Ultrasonics 8
- Statistical and Nonlinear Physics 41
- Computational Mechanics 67
Countries citing papers authored by Carlos A. Riofrío
This map shows the geographic impact of Carlos A. Riofrío'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 Carlos A. Riofrío with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carlos A. Riofrío more than expected).
Fields of papers citing papers by Carlos A. Riofrío
This network shows the impact of papers produced by Carlos A. Riofrío. 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 Carlos A. Riofrío. The network helps show where Carlos A. Riofrío may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Carlos A. Riofrío, 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 | 2024 | 6 | |
| 2 | 2024 | 2 | |
| 3 | 2023 | 10 | |
| 4 | 2023 | 0 | |
| 5 | 2018 | 15 | |
| 6 | 2017 | 96 | |
| 7 | 2017 | 29 | |
| 8 | 2016 | 2 | |
| 9 | 2015 | 22 | |
| 10 | 2015 | 64 | |
| 11 | 2014 | 19 | |
| 12 | 2014 | 10 | |
| 13 | 2014 | 10 | |
| 14 | 2013 | 41 | |
| 15 | 2013 | 47 | |
| 16 | 2011 | 15 | |
| 17 | 2010 | 24 |
About Carlos A. Riofrío
Carlos A. Riofrío is a scholar working on Computational Mathematics, Acoustics and Ultrasonics, Atomic and Molecular Physics, and Optics, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 17 papers that have together received 412 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (10 papers), Quantum Computing Algorithms and Architecture (8 papers), Quantum many-body systems (7 papers), Cold Atom Physics and Bose-Einstein Condensates (6 papers), Sparse and Compressive Sensing Techniques (3 papers), Quantum Mechanics and Applications (3 papers), Atomic and Subatomic Physics Research (2 papers) and Quantum chaos and dynamical systems (2 papers). The work is most often cited by research in Artificial Intelligence (339 citations), Atomic and Molecular Physics, and Optics (290 citations), Acoustics and Ultrasonics (8 citations), Statistical and Nonlinear Physics (41 citations) and Computational Mechanics (67 citations). Carlos A. Riofrío has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Ivan Deutsch, Poul Jessen, B. E. Anderson, Jens Eisert, Steven T. Flammia, Aaron Smith, Thomas Monz, Daniel Nigg, R. Blatt and Seth Merkel. Their work appears in journals such as Physical Review Letters, Physical Review A, Nature Communications, Quantum Science and Technology and Scientific Reports.
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.