M. C. Thom
Impact in
- Artificial Intelligence top 5%
- Quantum Information and Cryptography
- Quantum Computing Algorithms and Architecture
- Neural Networks and Reservoir Computing
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- Quantum and electron transport phenomena
- Quantum Mechanics and Applications
- Quantum many-body systems
Papers in
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- Quantum Information and Cryptography 4
- Quantum Computing Algorithms and Architecture 3
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- Quantum and electron transport phenomena 4
- Spectroscopy and Quantum Chemical Studies 1
- Co-authors
- S. Uchaikin (4 shared papers)R. Harris (4 shared papers)P. Bunyk (4 shared papers)A. J. Berkley (4 shared papers)Mark W. Johnson (4 shared papers)M. H. S. Amin (3 shared papers)E. Ladizinsky (3 shared papers)Siyuan Han (2 shared papers)
- Journals
- Physical Review Letters (2 papers)Physical Review B (2 papers)PubMed Central (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
M. C. Thom
6 papers receiving 255 citations
Peers
Comparison fields: 5 of 35
- Artificial Intelligence 220
- Atomic and Molecular Physics, and Optics 196
- Condensed Matter Physics 32
- Statistical and Nonlinear Physics 17
- Computational Theory and Mathematics 17
Countries citing papers authored by M. C. Thom
This map shows the geographic impact of M. C. Thom'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. C. Thom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. C. Thom more than expected).
Fields of papers citing papers by M. C. Thom
This network shows the impact of papers produced by M. C. Thom. 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. C. Thom. The network helps show where M. C. Thom may publish in the future.
Co-authors
The 25 scholars most cited alongside M. C. Thom, 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 | 2010 | 112 | |
| 2 | 2007 | 81 | |
| 3 | 2008 | 55 | |
| 4 | 2007 | 12 | |
| 5 | 2010 | 10 | |
| 6 | 2021 | 3 |
About M. C. Thom
M. C. Thom is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Condensed Matter Physics, Information Systems and Computer Vision and Pattern Recognition, having authored 6 papers that have together received 273 indexed citations. Recurring topics across this work include Quantum and electron transport phenomena (4 papers), Quantum Information and Cryptography (4 papers), Quantum Computing Algorithms and Architecture (3 papers), Physics of Superconductivity and Magnetism (1 paper), Cloud Computing and Resource Management (1 paper), Robotics and Sensor-Based Localization (1 paper), Spectroscopy and Quantum Chemical Studies (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Artificial Intelligence (220 citations), Atomic and Molecular Physics, and Optics (196 citations), Condensed Matter Physics (32 citations), Statistical and Nonlinear Physics (17 citations) and Computational Theory and Mathematics (17 citations). M. C. Thom has collaborated with scholars based in United States and Germany. Frequent co-authors include S. Uchaikin, R. Harris, P. Bunyk, A. J. Berkley, Mark W. Johnson, M. H. S. Amin, E. Ladizinsky, Siyuan Han, S. A. Govorkov and A. B. Wilson. Their work appears in journals such as Physical Review Letters, Physical Review B and PubMed Central.
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.