Luca Perniè
- Nuclear and High Energy Physics
- Astronomy and Astrophysics
- Artificial Intelligence
- Computer Networks and Communications
- Radiation
- Co-authors
- José Miguel NoMichael SpannowskyTao HuangMichael J. Ramsey-MusolfPeter WinslowA. SafonovP. MarageL. Favart
- Topics
- Particle physics theoretical and experimental studies (4 papers)High-Energy Particle Collisions Research (2 papers)Particle Detector Development and Performance (2 papers)
- Journals
- Physical review. DDépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles)
- Partner nations
- United KingdomUnited States
In The Last Decade
Luca Perniè
3 papers receiving 59 citations
Peers
Comparison fields: 5 of 6
- Nuclear and High Energy Physics 60
- Astronomy and Astrophysics 31
- Artificial Intelligence 8
- Computer Networks and Communications 2
- Radiation 1
Countries citing papers authored by Luca Perniè
This map shows the geographic impact of Luca Perniè'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 Luca Perniè with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luca Perniè more than expected).
Fields of papers citing papers by Luca Perniè
This network shows the impact of papers produced by Luca Perniè. 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 Luca Perniè. The network helps show where Luca Perniè may publish in the future.
Co-authorship network of co-authors of Luca Perniè
This figure shows the co-authorship network connecting the top 25 collaborators of Luca Perniè. A scholar is included among the top collaborators of Luca Perniè 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 Luca Perniè. Luca Perniè is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 50 | |
| 2 | Description and performance of track and primary-vertex reconstruction with the CMS tracker: JINST 9 (2014) 10, P10009 | 7 |
| 3 | Inclusive search for a fourth generation of quarks with the CMS experiment | 3 |
| 4 | Top pair cross section in lepton+jets+btag | 0 |
| 5 | Search for single top production in the tW-channel | 0 |
About Luca Perniè
Luca Perniè is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Artificial Intelligence, having authored 5 papers that have together received 60 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (4 papers), High-Energy Particle Collisions Research (2 papers) and Particle Detector Development and Performance (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (60 citations), Astronomy and Astrophysics (31 citations) and Artificial Intelligence (8 citations). Luca Perniè has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include José Miguel No, Michael Spannowsky, Tao Huang, Michael J. Ramsey-Musolf, Peter Winslow, A. Safonov, P. Marage, L. Favart, P. Vanlaer and B. Clerbaux. Their work appears in journals such as Physical review. D and Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles).
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.