Jonas Bylander
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- Quantum and electron transport phenomena 30
- Mechanical and Optical Resonators 6
- Quantum optics and atomic interactions 5
- Cold Atom Physics and Bose-Einstein Condensates 4
- Artificial Intelligence top 1%
- Quantum Information and Cryptography 31
- Quantum Computing Algorithms and Architecture 18
- Neural Networks and Reservoir Computing 4
- Condensed Matter Physics top 10%
- Physics of Superconductivity and Magnetism 7
Jonas Bylander
47 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 69
- Atomic and Molecular Physics, and Optics 1.5k
- Artificial Intelligence 1.2k
- Condensed Matter Physics 138
- Statistical and Nonlinear Physics 89
- Electrical and Electronic Engineering 294
Countries citing papers authored by Jonas Bylander
This map shows the geographic impact of Jonas Bylander'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 Jonas Bylander with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonas Bylander more than expected).
Fields of papers citing papers by Jonas Bylander
This network shows the impact of papers produced by Jonas Bylander. 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 Jonas Bylander. The network helps show where Jonas Bylander may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jonas Bylander, 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 | 8 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 14 | |
| 5 | 2023 | 42 | |
| 6 | 2023 | 9 | |
| 7 | 2023 | 18 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 4 | |
| 10 | 2023 | 16 | |
| 11 | 2023 | 21 | |
| 12 | 2022 | 54 | |
| 13 | 2021 | 59 | |
| 14 | 2021 | 24 | |
| 15 | 2020 | 4 | |
| 16 | Quantum approximate optimization of the exact-cover problem on a superconducting quantum processor | 2019 | 4 |
| 17 | 2016 | 60 | |
| 18 | Z-Gate Operation on a Superconducting Flux Qubit via Its Readout SQUID | 2015 | 1 |
| 19 | 2013 | 17 | |
| 20 | Current measurement by real-time counting of single charges | 2005 | 0 |
About Jonas Bylander
Jonas Bylander is a scholar working on Atomic and Molecular Physics, and Optics, Acoustics and Ultrasonics, Artificial Intelligence, Condensed Matter Physics and Astronomy and Astrophysics, having authored 48 papers that have together received 1.7k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (31 papers), Quantum and electron transport phenomena (30 papers), Quantum Computing Algorithms and Architecture (18 papers), Physics of Superconductivity and Magnetism (7 papers), Mechanical and Optical Resonators (6 papers), Quantum optics and atomic interactions (5 papers), Cold Atom Physics and Bose-Einstein Condensates (4 papers) and Neural Networks and Reservoir Computing (4 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (1.5k citations), Artificial Intelligence (1.2k citations), Condensed Matter Physics (138 citations), Statistical and Nonlinear Physics (89 citations) and Electrical and Electronic Engineering (294 citations). Jonas Bylander has collaborated with scholars based in Sweden, United States and Japan. Frequent co-authors include William D. Oliver, Simon Gustavsson, Per Delsing, Fumiki Yoshihara, Yasunobu Nakamura, Fei Yan, David G. Cory, T. Duty, K. Harrabi and George Fitch. Their work appears in journals such as Physical Review B, Physical Review Letters, npj Quantum Information, Physical Review Applied and PRX Quantum.
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.