Andrew Sornborger
- Artificial Intelligence top 1%
- Atomic and Molecular Physics, and Optics top 5%
- Astronomy and Astrophysics top 5%
- Nuclear and High Energy Physics top 5%
- Cognitive Neuroscience top 10%
- Co-authors
- Patrick J. ColesŁukasz CincioZoë HolmesRobert BrandenbergerViatcheslav MukhanovC. MatthiasHsin-Yuan HuangM. Cerezo
- Topics
- Neural dynamics and brain function (27 papers)Quantum Computing Algorithms and Architecture (23 papers)Quantum Information and Cryptography (22 papers)
- Journals
- Physical Review LettersNature CommunicationsSHILAP Revista de lepidopterología
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Andrew Sornborger
88 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Artificial Intelligence 953
- Atomic and Molecular Physics, and Optics 492
- Astronomy and Astrophysics 299
- Nuclear and High Energy Physics 286
- Cognitive Neuroscience 199
Countries citing papers authored by Andrew Sornborger
This map shows the geographic impact of Andrew Sornborger'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 Andrew Sornborger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Sornborger more than expected).
Fields of papers citing papers by Andrew Sornborger
This network shows the impact of papers produced by Andrew Sornborger. 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 Andrew Sornborger. The network helps show where Andrew Sornborger may publish in the future.
Co-authorship network of co-authors of Andrew Sornborger
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Sornborger. A scholar is included among the top collaborators of Andrew Sornborger 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 Andrew Sornborger. Andrew Sornborger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 13 | |
| 3 | 4 | |
| 4 | 19 | |
| 5 | 26 | |
| 6 | 1 | |
| 7 | Generalization in quantum machine learning from few training databreakdown → | 244 |
| 8 | 20 | |
| 9 | 37 | |
| 10 | 15 | |
| 11 | 10 | |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 20 | |
| 15 | 4 | |
| 16 | 3 | |
| 17 | 52 | |
| 18 | 16 | |
| 19 | 3 | |
| 20 | Persistence Amplitudes from Numerical Quantum Gravity | 3 |
About Andrew Sornborger
Andrew Sornborger is a scholar working on Equine, Biophysics and Cognitive Neuroscience, having authored 94 papers that have together received 1.8k indexed citations. Recurring topics across this work include Neural dynamics and brain function (27 papers), Quantum Computing Algorithms and Architecture (23 papers) and Quantum Information and Cryptography (22 papers). The work is most often cited by research in Artificial Intelligence (953 citations), Equine (39 citations) and Nuclear and High Energy Physics (286 citations). Andrew Sornborger has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Patrick J. Coles, Łukasz Cincio, Zoë Holmes, Robert Brandenberger, Viatcheslav Mukhanov, C. Matthias, Hsin-Yuan Huang, M. Cerezo, Kunal Sharma and Sumeet Khatri. Their work appears in journals such as Physical Review Letters, Nature Communications and SHILAP Revista de lepidopterología.
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.