Patrick Tunney
Impact in
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- Particle physics theoretical and experimental studies
- Dark Matter and Cosmic Phenomena
- Neutrino Physics Research
- Quantum Chromodynamics and Particle Interactions
- Particle Detector Development and Performance
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- Domain Adaptation and Few-Shot Learning
- Anomaly Detection Techniques and Applications
Papers in
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- Particle physics theoretical and experimental studies 6
- Dark Matter and Cosmic Phenomena 5
- Co-authors
- Malcolm Fairbairn (3 shared papers)Felix Kahlhoefer (3 shared papers)Michael Krämer (2 shared papers)John R. Ellis (1 shared paper)José Miguel No (1 shared paper)Michael Duerr (1 shared paper)Christopher Hearty (1 shared paper)Kai Schmidt-Hoberg (1 shared paper)
- Journals
- Journal of High Energy Physics (3 papers)Physics of the Dark Universe (1 paper)Physical review. D (1 paper)Desy publication database (The Deutsches Elektronen-Synchrotron) (1 paper)RWTH Publications (RWTH Aachen) (1 paper)
- Partner nations
- GermanyUnited KingdomSwitzerland
In The Last Decade
Patrick Tunney
7 papers receiving 263 citations
Peers
Comparison fields: 2 of 2
- Nuclear and High Energy Physics 281
- Artificial Intelligence 2
Countries citing papers authored by Patrick Tunney
This map shows the geographic impact of Patrick Tunney'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 Patrick Tunney with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Tunney more than expected).
Fields of papers citing papers by Patrick Tunney
This network shows the impact of papers produced by Patrick Tunney. 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 Patrick Tunney. The network helps show where Patrick Tunney may publish in the future.
Co-authors
The 9 scholars most cited alongside Patrick Tunney, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Invisible and displaced dark matter signatures at Belle II | 2019 | 55 |
| 2 | 2019 | 52 | |
| 3 | 2020 | 50 | |
| 4 | 2016 | 46 | |
| 5 | 2017 | 38 | |
| 6 | 2017 | 30 | |
| 7 | On the challenges of searching for GeV-scale long-lived particles at the LHC | 2021 | 10 |
About Patrick Tunney
Patrick Tunney 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 7 papers that have together received 281 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (6 papers) and Dark Matter and Cosmic Phenomena (5 papers). The work is most often cited by research in Nuclear and High Energy Physics (281 citations), Artificial Intelligence (2 citations), Nuclear Energy and Engineering (0 citations), Waste Management and Disposal (0 citations) and Infectious Diseases (0 citations). Patrick Tunney has collaborated with scholars based in Germany, United Kingdom and Switzerland. Frequent co-authors include Malcolm Fairbairn, Felix Kahlhoefer, Michael Krämer, John R. Ellis, José Miguel No, Michael Duerr, Christopher Hearty, Kai Schmidt-Hoberg and Torben Ferber. Their work appears in journals such as Journal of High Energy Physics, Physics of the Dark Universe, Physical review. D, Desy publication database (The Deutsches Elektronen-Synchrotron) and RWTH Publications (RWTH Aachen).
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.