M. Guilbaud
Impact in
- Nuclear and High Energy Physics top 10%
- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Dark Matter and Cosmic Phenomena
- Particle Detector Development and Performance
- Neutrino Physics Research
- Black Holes and Theoretical Physics
- Astronomy and Astrophysics top 10%
- Cosmology and Gravitation Theories
Papers in
-
- Particle physics theoretical and experimental studies 43
- High-Energy Particle Collisions Research 36
- Quantum Chromodynamics and Particle Interactions 25
- Dark Matter and Cosmic Phenomena 7
- Particle Detector Development and Performance 6
- Neutrino Physics Research 2
- Black Holes and Theoretical Physics 1
-
- Cosmology and Gravitation Theories 9
M. Guilbaud
42 papers receiving 1.4k citations
M. Guilbaud's Hit Papers
Peers
Comparison fields: 5 of 48
- Nuclear and High Energy Physics 1.8k
- Astronomy and Astrophysics 361
- Artificial Intelligence 68
- Atomic and Molecular Physics, and Optics 33
- Statistical and Nonlinear Physics 11
Countries citing papers authored by M. Guilbaud
This map shows the geographic impact of M. Guilbaud'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 M. Guilbaud with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Guilbaud more than expected).
Fields of papers citing papers by M. Guilbaud
This network shows the impact of papers produced by M. Guilbaud. 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 M. Guilbaud. The network helps show where M. Guilbaud may publish in the future.
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All Works
Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Extraction and validation of a new set of CMS pythia8 tunes from underlying-event measurements Hit paper breakdown → | 2020 | 279 |
| 2 | 2015 | 147 | |
| 3 | 2015 | 118 | |
| 4 | 2016 | 115 | |
| 5 | 2015 | 104 | |
| 6 | 2017 | 85 | |
| 7 | 2017 | 77 | |
| 8 | 2017 | 77 | |
| 9 | 2017 | 52 | |
| 10 | 2016 | 50 | |
| 11 | 2016 | 49 | |
| 12 | 2016 | 47 | |
| 13 | 2020 | 46 | |
| 14 | 2018 | 46 | |
| 15 | 2016 | 34 | |
| 16 | 2017 | 32 | |
| 17 | 2016 | 30 | |
| 18 | 2019 | 29 | |
| 19 | 2021 | 29 | |
| 20 | 2016 | 29 |
About M. Guilbaud
M. Guilbaud is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics, Insect Science, Renewable Energy, Sustainability and the Environment and Obstetrics and Gynecology, having authored 43 papers that have together received 1.8k indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (43 papers), High-Energy Particle Collisions Research (36 papers), Quantum Chromodynamics and Particle Interactions (25 papers), Cosmology and Gravitation Theories (9 papers), Dark Matter and Cosmic Phenomena (7 papers), Particle Detector Development and Performance (6 papers), Neutrino Physics Research (2 papers) and Black Holes and Theoretical Physics (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (1.8k citations), Astronomy and Astrophysics (361 citations), Artificial Intelligence (68 citations), Atomic and Molecular Physics, and Optics (33 citations) and Statistical and Nonlinear Physics (11 citations). M. Guilbaud has collaborated with scholars based in Austria, Serbia and United States. Their work appears in journals such as Journal of High Energy Physics, Physics Letters B, Physical Review Letters, Physical review. D and The European Physical Journal C.
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.