Francesco Arzani
- Artificial Intelligence top 5%
- Atomic and Molecular Physics, and Optics top 10%
- Electrical and Electronic Engineering
- Computational Theory and Mathematics
- Statistical and Nonlinear Physics
- Co-authors
- Nicolas TrepsClaude FabreGiulia FerriniJonathan RoslundYin CaiJens EisertXiao-Yun XuElies Gil-Fuster
- Topics
- Quantum Information and Cryptography (11 papers)Quantum Computing Algorithms and Architecture (6 papers)Quantum Mechanics and Applications (5 papers)
In The Last Decade
Francesco Arzani
14 papers receiving 424 citations
Hit Papers
Peers
Comparison fields: 5 of 34
- Artificial Intelligence 378
- Atomic and Molecular Physics, and Optics 318
- Electrical and Electronic Engineering 78
- Computational Theory and Mathematics 29
- Statistical and Nonlinear Physics 19
Countries citing papers authored by Francesco Arzani
This map shows the geographic impact of Francesco Arzani'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 Francesco Arzani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco Arzani more than expected).
Fields of papers citing papers by Francesco Arzani
This network shows the impact of papers produced by Francesco Arzani. 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 Francesco Arzani. The network helps show where Francesco Arzani may publish in the future.
Co-authorship network of co-authors of Francesco Arzani
This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Arzani. A scholar is included among the top collaborators of Francesco Arzani 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 Francesco Arzani. Francesco Arzani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Exploiting Symmetry in Variational Quantum Machine Learningbreakdown → | 101 |
| 2 | 24 | |
| 3 | 1 | |
| 4 | 23 | |
| 5 | 10 | |
| 6 | 7 | |
| 7 | 8 | |
| 8 | 34 | |
| 9 | 39 | |
| 10 | 145 | |
| 11 | 31 | |
| 12 | 7 | |
| 13 | 0 | |
| 14 | 19 | |
| 15 | 3 |
About Francesco Arzani
Francesco Arzani is a scholar working on Artificial Intelligence, Numerical Analysis and Atomic and Molecular Physics, and Optics, having authored 15 papers that have together received 452 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (11 papers), Quantum Computing Algorithms and Architecture (6 papers) and Quantum Mechanics and Applications (5 papers). The work is most often cited by research in Artificial Intelligence (378 citations), Atomic and Molecular Physics, and Optics (318 citations) and Acoustics and Ultrasonics (2 citations). Francesco Arzani has collaborated with scholars based in France, Germany and Iran. Frequent co-authors include Nicolas Treps, Claude Fabre, Giulia Ferrini, Jonathan Roslund, Yin Cai, Jens Eisert, Xiao-Yun Xu, Elies Gil-Fuster, Johannes Jakob Meyer and Antonio Anna Mele. Their work appears in journals such as Nature Communications, Physical Review A and New Journal of Physics.
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.