Mayer M. Feldman
- Atomic and Molecular Physics, and Optics top 10%
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Materials Chemistry
- Computational Theory and Mathematics
- Co-authors
- Michael J. GullansA. J. SigillitoJ. R. PettaAdam MillsErik NielsenJoseph KerckhoffClayton JacksonBorzoyeh Shojaei
- Topics
- Quantum and electron transport phenomena (3 papers)Quantum Computing Algorithms and Architecture (2 papers)Advancements in Semiconductor Devices and Circuit Design (1 paper)
- Cited by
- Atomic and Molecular Physics, and OpticsArtificial IntelligenceElectrical and Electronic Engineering
- Partner nations
- United StatesSweden
In The Last Decade
Mayer M. Feldman
4 papers receiving 240 citations
Hit Papers
Peers
Comparison fields: 5 of 15
- Atomic and Molecular Physics, and Optics 216
- Electrical and Electronic Engineering 123
- Artificial Intelligence 121
- Materials Chemistry 24
- Computational Theory and Mathematics 18
Countries citing papers authored by Mayer M. Feldman
This map shows the geographic impact of Mayer M. Feldman'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 Mayer M. Feldman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mayer M. Feldman more than expected).
Fields of papers citing papers by Mayer M. Feldman
This network shows the impact of papers produced by Mayer M. Feldman. 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 Mayer M. Feldman. The network helps show where Mayer M. Feldman may publish in the future.
Co-authorship network of co-authors of Mayer M. Feldman
This figure shows the co-authorship network connecting the top 25 collaborators of Mayer M. Feldman. A scholar is included among the top collaborators of Mayer M. Feldman 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 Mayer M. Feldman. Mayer M. Feldman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Two-qubit silicon quantum processor with operation fidelity exceeding 99%breakdown → | 196 |
| 2 | 31 | |
| 3 | 16 | |
| 4 | 1 |
About Mayer M. Feldman
Mayer M. Feldman is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence and Electronic, Optical and Magnetic Materials, having authored 4 papers that have together received 244 indexed citations. Recurring topics across this work include Quantum and electron transport phenomena (3 papers), Quantum Computing Algorithms and Architecture (2 papers) and Advancements in Semiconductor Devices and Circuit Design (1 paper). The work is most often cited by research in Atomic and Molecular Physics, and Optics (216 citations), Artificial Intelligence (121 citations) and Electrical and Electronic Engineering (123 citations). Mayer M. Feldman has collaborated with scholars based in United States and Sweden. Frequent co-authors include Michael J. Gullans, A. J. Sigillito, J. R. Petta, Adam Mills, Erik Nielsen, Joseph Kerckhoff, Clayton Jackson, Borzoyeh Shojaei, Matthew T. Rakher and Joon Sue Lee. Their work appears in journals such as Applied Physics Letters, Science Advances and Physical Review Applied.
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.