S. Vallecorsa
- Artificial Intelligence top 5%
- Nuclear and High Energy Physics top 10%
- Atomic and Molecular Physics, and Optics
- Computer Vision and Pattern Recognition top 10%
- Computational Theory and Mathematics top 10%
- Co-authors
- Michele GrossiFederico CarminatiElías F. CombarroAntonio MandarinoCenk TüysüzJosé RanillaF. SánchezPavel Lougovski
- Topics
- Quantum Computing Algorithms and Architecture (30 papers)Quantum Information and Cryptography (17 papers)Particle physics theoretical and experimental studies (15 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessNew Journal of Physics
- Partner nations
- SwitzerlandSpainUnited States
In The Last Decade
S. Vallecorsa
50 papers receiving 561 citations
Peers
Comparison fields: 5 of 52
- Artificial Intelligence 380
- Nuclear and High Energy Physics 148
- Atomic and Molecular Physics, and Optics 137
- Computer Vision and Pattern Recognition 59
- Computational Theory and Mathematics 53
Countries citing papers authored by S. Vallecorsa
This map shows the geographic impact of S. Vallecorsa'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 S. Vallecorsa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Vallecorsa more than expected).
Fields of papers citing papers by S. Vallecorsa
This network shows the impact of papers produced by S. Vallecorsa. 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 S. Vallecorsa. The network helps show where S. Vallecorsa may publish in the future.
Co-authorship network of co-authors of S. Vallecorsa
This figure shows the co-authorship network connecting the top 25 collaborators of S. Vallecorsa. A scholar is included among the top collaborators of S. Vallecorsa 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 S. Vallecorsa. S. Vallecorsa 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 | 21 | |
| 3 | 9 | |
| 4 | 16 | |
| 5 | 4 | |
| 6 | 9 | |
| 7 | 6 | |
| 8 | 0 | |
| 9 | 4 | |
| 10 | 24 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 11 | |
| 14 | 32 | |
| 15 | 0 | |
| 16 | 1 | |
| 17 | 37 | |
| 18 | 4 | |
| 19 | 1 | |
| 20 | 14 |
About S. Vallecorsa
S. Vallecorsa is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence and Hardware and Architecture, having authored 58 papers that have together received 569 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (30 papers), Quantum Information and Cryptography (17 papers) and Particle physics theoretical and experimental studies (15 papers). The work is most often cited by research in Artificial Intelligence (380 citations), Nuclear and High Energy Physics (148 citations) and Computational Mathematics (3 citations). S. Vallecorsa has collaborated with scholars based in Switzerland, Spain and United States. Frequent co-authors include Michele Grossi, Federico Carminati, Elías F. Combarro, Antonio Mandarino, Cenk Tüysüz, José Ranilla, F. Sánchez, Pavel Lougovski, Xi Li and Chen Wu. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access 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.