Nathan Earnest
- Artificial Intelligence top 5%
- Atomic and Molecular Physics, and Optics top 10%
- Electrical and Electronic Engineering
- Computational Theory and Mathematics
- Condensed Matter Physics
- Co-authors
- Nelson L. C. LeungSrivatsan ChakramRavi NaikYao LuJens KochDavid SchusterPeter GroszkowskiDavid McKay
- Topics
- Quantum Information and Cryptography (12 papers)Quantum Computing Algorithms and Architecture (9 papers)Quantum and electron transport phenomena (7 papers)
- Cited by
- Artificial IntelligenceAtomic and Molecular Physics, and OpticsComputational Theory and Mathematics
- Partner nations
- United StatesNetherlandsSwitzerland
In The Last Decade
Nathan Earnest
14 papers receiving 407 citations
Peers
Comparison fields: 5 of 24
- Artificial Intelligence 355
- Atomic and Molecular Physics, and Optics 336
- Electrical and Electronic Engineering 28
- Computational Theory and Mathematics 24
- Condensed Matter Physics 17
Countries citing papers authored by Nathan Earnest
This map shows the geographic impact of Nathan Earnest'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 Nathan Earnest with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan Earnest more than expected).
Fields of papers citing papers by Nathan Earnest
This network shows the impact of papers produced by Nathan Earnest. 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 Nathan Earnest. The network helps show where Nathan Earnest may publish in the future.
Co-authorship network of co-authors of Nathan Earnest
This figure shows the co-authorship network connecting the top 25 collaborators of Nathan Earnest. A scholar is included among the top collaborators of Nathan Earnest 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 Nathan Earnest. Nathan Earnest is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 10 | |
| 3 | 10 | |
| 4 | 25 | |
| 5 | 4 | |
| 6 | 28 | |
| 7 | 9 | |
| 8 | 0 | |
| 9 | Toffoli Gate Depth Reduction in Fixed Frequency Transmon Qutrits | 2 |
| 10 | 61 | |
| 11 | 1 | |
| 12 | 76 | |
| 13 | 9 | |
| 14 | 89 | |
| 15 | 87 |
About Nathan Earnest
Nathan Earnest is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Bioengineering, having authored 15 papers that have together received 414 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (12 papers), Quantum Computing Algorithms and Architecture (9 papers) and Quantum and electron transport phenomena (7 papers). The work is most often cited by research in Artificial Intelligence (355 citations), Atomic and Molecular Physics, and Optics (336 citations) and Computational Theory and Mathematics (24 citations). Nathan Earnest has collaborated with scholars based in United States, Netherlands and Switzerland. Frequent co-authors include Nelson L. C. Leung, Srivatsan Chakram, Ravi Naik, Yao Lu, Jens Koch, David Schuster, Peter Groszkowski, David McKay, Ziwen Huang and Eliot Kapit. Their work appears in journals such as Physical Review Letters, Nature Communications and Physical review. A.
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.