Gianluca Passarelli
- Atomic and Molecular Physics, and Optics top 10%
- Artificial Intelligence top 10%
- Statistical and Nonlinear Physics top 10%
- Condensed Matter Physics
- Computational Theory and Mathematics
- Co-authors
- Procolo LucignanoRosario FazioV. CataudellaAngelo RussomannoDaniel A. LidarHidetoshi NishimoriG. De FilippisDavide Rossini
- Topics
- Quantum Information and Cryptography (14 papers)Quantum Computing Algorithms and Architecture (13 papers)Quantum many-body systems (11 papers)
- Cited by
- Atomic and Molecular Physics, and OpticsArtificial IntelligenceStatistical and Nonlinear Physics
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Gianluca Passarelli
21 papers receiving 248 citations
Peers
Comparison fields: 5 of 28
- Atomic and Molecular Physics, and Optics 170
- Artificial Intelligence 162
- Statistical and Nonlinear Physics 43
- Condensed Matter Physics 23
- Computational Theory and Mathematics 21
Countries citing papers authored by Gianluca Passarelli
This map shows the geographic impact of Gianluca Passarelli'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 Gianluca Passarelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gianluca Passarelli more than expected).
Fields of papers citing papers by Gianluca Passarelli
This network shows the impact of papers produced by Gianluca Passarelli. 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 Gianluca Passarelli. The network helps show where Gianluca Passarelli may publish in the future.
Co-authorship network of co-authors of Gianluca Passarelli
This figure shows the co-authorship network connecting the top 25 collaborators of Gianluca Passarelli. A scholar is included among the top collaborators of Gianluca Passarelli 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 Gianluca Passarelli. Gianluca Passarelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 6 | |
| 4 | 10 | |
| 5 | 5 | |
| 6 | 24 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 5 | |
| 10 | 7 | |
| 11 | 6 | |
| 12 | 8 | |
| 13 | 24 | |
| 14 | 20 | |
| 15 | 5 | |
| 16 | 7 | |
| 17 | 33 | |
| 18 | 28 | |
| 19 | 5 | |
| 20 | 21 |
About Gianluca Passarelli
Gianluca Passarelli is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence and Geometry and Topology, having authored 22 papers that have together received 254 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (14 papers), Quantum Computing Algorithms and Architecture (13 papers) and Quantum many-body systems (11 papers). The work is most often cited by research in Atomic and Molecular Physics, and Optics (170 citations), Artificial Intelligence (162 citations) and Statistical and Nonlinear Physics (43 citations). Gianluca Passarelli has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Procolo Lucignano, Rosario Fazio, V. Cataudella, Angelo Russomanno, Daniel A. Lidar, Hidetoshi Nishimori, G. De Filippis, Davide Rossini, Xhek Turkeshi and Marco Schiró. Their work appears in journals such as Physical Review Letters, Applied Soft Computing 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.