M. Link
Impact in
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- Physics of Superconductivity and Magnetism
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- Cold Atom Physics and Bose-Einstein Condensates
- Quantum, superfluid, helium dynamics
- Atomic and Subatomic Physics Research
- Quantum many-body systems
- Quantum and electron transport phenomena
- Quantum optics and atomic interactions
Papers in
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- Cold Atom Physics and Bose-Einstein Condensates 4
- Quantum, superfluid, helium dynamics 4
- Atomic and Subatomic Physics Research 2
- Quantum many-body systems 1
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- Physics of Superconductivity and Magnetism 1
- Co-authors
- Michael Köhl (4 shared papers)K. Gao (4 shared papers)Corinna Kollath (1 shared paper)Jean-Sébastien Bernier (1 shared paper)Benjamin Rauf (1 shared paper)Axel Hoffmann (1 shared paper)Max Schwarz (1 shared paper)Sven Behnke (1 shared paper)
- Journals
- Review of Scientific Instruments (1 paper)Physical review. A (1 paper)Physical Review Letters (1 paper)Nature Physics (1 paper)2022 International Joint Conference on Neural Networks (IJCNN) (1 paper)
In The Last Decade
M. Link
5 papers receiving 83 citations
Peers
Comparison fields: 5 of 20
- Condensed Matter Physics 32
- Atomic and Molecular Physics, and Optics 79
- Spectroscopy 3
- Biophysics 1
- Artificial Intelligence 6
Countries citing papers authored by M. Link
This map shows the geographic impact of M. Link'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 M. Link with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Link more than expected).
Fields of papers citing papers by M. Link
This network shows the impact of papers produced by M. Link. 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 M. Link. The network helps show where M. Link may publish in the future.
Co-authors
The 8 scholars most cited alongside M. Link, 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 | 2018 | 64 | |
| 2 | 2023 | 12 | |
| 3 | 2021 | 7 | |
| 4 | 2023 | 1 | |
| 5 | 2022 | 1 |
About M. Link
M. Link is a scholar working on Atomic and Molecular Physics, and Optics, Condensed Matter Physics, Computer Vision and Pattern Recognition, Infectious Diseases and Organic Chemistry, having authored 5 papers that have together received 85 indexed citations. Recurring topics across this work include Cold Atom Physics and Bose-Einstein Condensates (4 papers), Quantum, superfluid, helium dynamics (4 papers), Atomic and Subatomic Physics Research (2 papers), Physics of Superconductivity and Magnetism (1 paper), Quantum many-body systems (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper), Human Pose and Action Recognition (1 paper) and Advanced Neural Network Applications (1 paper). The work is most often cited by research in Condensed Matter Physics (32 citations), Atomic and Molecular Physics, and Optics (79 citations), Spectroscopy (3 citations), Biophysics (1 citation) and Artificial Intelligence (6 citations). M. Link has collaborated with scholars based in Germany and China. Frequent co-authors include Michael Köhl, K. Gao, Corinna Kollath, Jean-Sébastien Bernier, Benjamin Rauf, Axel Hoffmann, Max Schwarz and Sven Behnke. Their work appears in journals such as Review of Scientific Instruments, Physical review. A, Physical Review Letters, Nature Physics and 2022 International Joint Conference on Neural Networks (IJCNN).
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.