M. C. Thom
Impact in
- Artificial Intelligence top 10%
- Quantum Information and Cryptography
- Quantum Computing Algorithms and Architecture
- Neural Networks and Reservoir Computing
-
- Quantum and electron transport phenomena
- Quantum Mechanics and Applications
- Quantum many-body systems
Papers in
-
- Quantum Information and Cryptography 4
- Quantum Computing Algorithms and Architecture 3
-
- Quantum and electron transport phenomena 4
- Spectroscopy and Quantum Chemical Studies 1
- Co-authors
- P. Bunyk (4 shared papers)R. Harris (4 shared papers)A. J. Berkley (4 shared papers)Mark W. Johnson (4 shared papers)S. Uchaikin (4 shared papers)E. Ladizinsky (3 shared papers)Siyuan Han (2 shared papers)M. H. S. Amin (3 shared papers)
- Journals
- Physical Review B (2 papers)Physical Review Letters (2 papers)PubMed Central (1 paper)
- Partner nations
- CanadaUnited StatesGermany
In The Last Decade
M. C. Thom
6 papers receiving 275 citations
Peers
Comparison fields: 5 of 36
- Artificial Intelligence 227
- Atomic and Molecular Physics, and Optics 200
- Condensed Matter Physics 32
- Statistical and Nonlinear Physics 17
- Computational Theory and Mathematics 18
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 | 115 | |
| 2 | 2007 | 84 | |
| 3 | 2008 | 56 | |
| 4 | 2007 | 12 | |
| 5 | 2010 | 11 | |
| 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 281 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (4 papers), Quantum and electron transport phenomena (4 papers), Quantum Computing Algorithms and Architecture (3 papers), Cloud Computing and Resource Management (1 paper), Advanced Vision and Imaging (1 paper), Spectroscopy and Quantum Chemical Studies (1 paper), Robotic Path Planning Algorithms (1 paper) and Physics of Superconductivity and Magnetism (1 paper). The work is most often cited by research in Artificial Intelligence (227 citations), Atomic and Molecular Physics, and Optics (200 citations), Condensed Matter Physics (32 citations), Statistical and Nonlinear Physics (17 citations) and Computational Theory and Mathematics (18 citations). M. C. Thom has collaborated with scholars based in Canada, United States and Germany. Frequent co-authors include P. Bunyk, R. Harris, A. J. Berkley, Mark W. Johnson, S. Uchaikin, E. Ladizinsky, Siyuan Han, M. H. S. Amin, S. A. Govorkov and T. Lanting. Their work appears in journals such as Physical Review B, Physical Review Letters 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.