Roger G. Melko
- Atomic and Molecular Physics, and Optics top 0.5%
- Condensed Matter Physics top 0.2%
- Artificial Intelligence top 0.5%
- Statistical and Nonlinear Physics top 0.5%
- Materials Chemistry top 5%
- Co-authors
- Juan CarrasquillaGiacomo TorlaiMatthew B. HastingsMichel J. P. GingrasAnn B. KallinRibhu K. KaulSergei V. IsakovB. C. den Hertog
- Topics
- Quantum many-body systems (74 papers)Physics of Superconductivity and Magnetism (48 papers)Advanced Condensed Matter Physics (31 papers)
- Cited by
- Condensed Matter PhysicsAtomic and Molecular Physics, and OpticsStatistical and Nonlinear Physics
- Partner nations
- CanadaUnited StatesGermany
In The Last Decade
Roger G. Melko
126 papers receiving 6.2k citations
Hit Papers
Peers
Comparison fields: 5 of 124
- Atomic and Molecular Physics, and Optics 3.9k
- Condensed Matter Physics 3.2k
- Artificial Intelligence 1.6k
- Statistical and Nonlinear Physics 1.0k
- Materials Chemistry 949
Countries citing papers authored by Roger G. Melko
This map shows the geographic impact of Roger G. Melko'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 Roger G. Melko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roger G. Melko more than expected).
Fields of papers citing papers by Roger G. Melko
This network shows the impact of papers produced by Roger G. Melko. 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 Roger G. Melko. The network helps show where Roger G. Melko may publish in the future.
Co-authorship network of co-authors of Roger G. Melko
This figure shows the co-authorship network connecting the top 25 collaborators of Roger G. Melko. A scholar is included among the top collaborators of Roger G. Melko based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Roger G. Melko. Roger G. Melko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 4 | |
| 8 | 10 | |
| 9 | 13 | |
| 10 | 117 | |
| 11 | Deep Learning the Ising Model Near Criticality | 17 |
| 12 | Machine Learning Z 2 Quantum Spin Liquids with Quasi-particle Statistics | 4 |
| 13 | Quantum Boltzmann Machine | 16 |
| 14 | 34 | |
| 15 | 7 | |
| 16 | 85 | |
| 17 | 22 | |
| 18 | 18 | |
| 19 | 57 | |
| 20 | 248 |
About Roger G. Melko
Roger G. Melko is a scholar working on Condensed Matter Physics, Atomic and Molecular Physics, and Optics and Statistical and Nonlinear Physics, having authored 130 papers that have together received 6.3k indexed citations. Recurring topics across this work include Quantum many-body systems (74 papers), Physics of Superconductivity and Magnetism (48 papers) and Advanced Condensed Matter Physics (31 papers). The work is most often cited by research in Condensed Matter Physics (3.2k citations), Atomic and Molecular Physics, and Optics (3.9k citations) and Statistical and Nonlinear Physics (1.0k citations). Roger G. Melko has collaborated with scholars based in Canada, United States and Germany. Frequent co-authors include Juan Carrasquilla, Giacomo Torlai, Matthew B. Hastings, Michel J. P. Gingras, Ann B. Kallin, Ribhu K. Kaul, Sergei V. Isakov, B. C. den Hertog, Iván González and Stephen Inglis. Their work appears in journals such as Science, Physical Review Letters and Nature Communications.
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.