M. Racko
Impact in
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- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Particle Detector Development and Performance
- Dark Matter and Cosmic Phenomena
- Quantum Chromodynamics and Particle Interactions
- Neutrino Physics Research
- Nuclear physics research studies
Papers in
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- Particle physics theoretical and experimental studies 115
- High-Energy Particle Collisions Research 12
- Particle Detector Development and Performance 9
M. Racko
128 papers receiving 3.9k citations
M. Racko's Hit Papers
Peers
Comparison fields: 5 of 29
- Nuclear and High Energy Physics 4.7k
- Statistical and Nonlinear Physics 24
- Information Systems and Management 18
- Artificial Intelligence 60
- Astronomy and Astrophysics 29
Countries citing papers authored by M. Racko
This map shows the geographic impact of M. Racko'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. Racko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Racko more than expected).
Fields of papers citing papers by M. Racko
This network shows the impact of papers produced by M. Racko. 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. Racko. The network helps show where M. Racko may publish in the future.
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All Works
Showing the 20 most-cited of 131 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | ATLAS b-jet identification performance and efficiency measurement with $$t{\bar{t}}$$ events in pp collisions at $$\sqrt{s}=13$$ TeV Hit paper breakdown → | 2019 | 250 |
| 2 | Performance of electron and photon triggers in ATLAS during LHC Run 2 Hit paper breakdown → | 2020 | 219 |
| 3 | Muon reconstruction and identification efficiency in ATLAS using the full Run 2 pp collision data set at $$\sqrt{s}=13$$ TeV Hit paper breakdown → | 2021 | 209 |
| 4 | Jet energy scale and resolution measured in proton–proton collisions at $$\sqrt{s}=13$$ TeV with the ATLAS detector Hit paper breakdown → | 2021 | 195 |
| 5 | 2020 | 156 | |
| 6 | 2020 | 154 | |
| 7 | 2021 | 116 | |
| 8 | 2020 | 112 | |
| 9 | 2020 | 110 | |
| 10 | 2020 | 94 | |
| 11 | 2019 | 88 | |
| 12 | 2021 | 81 | |
| 13 | 2021 | 78 | |
| 14 | 2020 | 74 | |
| 15 | 2020 | 66 | |
| 16 | 2020 | 66 | |
| 17 | 2021 | 66 | |
| 18 | 2021 | 63 | |
| 19 | 2020 | 61 | |
| 20 | 2020 | 61 |
About M. Racko
M. Racko is a scholar working on Nuclear and High Energy Physics, Nuclear Energy and Engineering, Waste Management and Disposal, Infectious Diseases and Organic Chemistry, having authored 131 papers that have together received 4.8k indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (115 papers), High-Energy Particle Collisions Research (12 papers) and Particle Detector Development and Performance (9 papers). The work is most often cited by research in Nuclear and High Energy Physics (4.7k citations), Statistical and Nonlinear Physics (24 citations), Information Systems and Management (18 citations), Artificial Intelligence (60 citations) and Astronomy and Astrophysics (29 citations). M. Racko has collaborated with scholars based in France, Australia and Switzerland. Their work appears in journals such as The European Physical Journal C, Journal of High Energy Physics, Physics Letters B, Physical review. D and Physical Review Letters.
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.