Nicholas T. Bronn
- Artificial Intelligence top 10%
- Atomic and Molecular Physics, and Optics
- Materials Chemistry
- Electronic, Optical and Magnetic Materials
- Electrical and Electronic Engineering
- Co-authors
- Nadya MasonLane W. MartinEric BreckenfeldAnoop R. DamodaranJ. KarthikSang LeeDavid PekkerJerry M. Chow
- Topics
- Quantum Computing Algorithms and Architecture (11 papers)Quantum Information and Cryptography (9 papers)Quantum and electron transport phenomena (8 papers)
- Cited by
- Electronic, Optical and Magnetic MaterialsArtificial IntelligenceAtomic and Molecular Physics, and Optics
- Partner nations
- United StatesNetherlandsGermany
In The Last Decade
Nicholas T. Bronn
18 papers receiving 325 citations
Peers
Comparison fields: 5 of 24
- Artificial Intelligence 164
- Atomic and Molecular Physics, and Optics 145
- Materials Chemistry 132
- Electronic, Optical and Magnetic Materials 101
- Electrical and Electronic Engineering 97
Countries citing papers authored by Nicholas T. Bronn
This map shows the geographic impact of Nicholas T. Bronn'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 Nicholas T. Bronn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas T. Bronn more than expected).
Fields of papers citing papers by Nicholas T. Bronn
This network shows the impact of papers produced by Nicholas T. Bronn. 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 Nicholas T. Bronn. The network helps show where Nicholas T. Bronn may publish in the future.
Co-authorship network of co-authors of Nicholas T. Bronn
This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas T. Bronn. A scholar is included among the top collaborators of Nicholas T. Bronn 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 Nicholas T. Bronn. Nicholas T. Bronn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 6 | |
| 3 | 8 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 7 | |
| 8 | 10 | |
| 9 | 4 | |
| 10 | 13 | |
| 11 | 43 | |
| 12 | 22 | |
| 13 | Enablement of near-term quantum processors by architectural yield engineering | 1 |
| 14 | 10 | |
| 15 | 44 | |
| 16 | 24 | |
| 17 | 13 | |
| 18 | 117 | |
| 19 | 6 |
About Nicholas T. Bronn
Nicholas T. Bronn is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Electronic, Optical and Magnetic Materials, having authored 19 papers that have together received 335 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (11 papers), Quantum Information and Cryptography (9 papers) and Quantum and electron transport phenomena (8 papers). The work is most often cited by research in Electronic, Optical and Magnetic Materials (101 citations), Artificial Intelligence (164 citations) and Atomic and Molecular Physics, and Optics (145 citations). Nicholas T. Bronn has collaborated with scholars based in United States, Netherlands and Germany. Frequent co-authors include Nadya Mason, Lane W. Martin, Eric Breckenfeld, Anoop R. Damodaran, J. Karthik, Sang Lee, David Pekker, Jerry M. Chow, Jay Gambetta and Daniel J. Egger. Their work appears in journals such as Physical Review Letters, Nature Communications and Applied Physics Letters.
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.