David Yu
Impact in
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- 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
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- Particle physics theoretical and experimental studies 763
- High-Energy Particle Collisions Research 102
- Particle Detector Development and Performance 51
- Quantum Chromodynamics and Particle Interactions 37
- Dark Matter and Cosmic Phenomena 4
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- Distributed and Parallel Computing Systems 3
- Co-authors
- Leslie J Rosenberg (1 shared paper)Richard F. Bradley (1 shared paper)P. Sikivie (1 shared paper)David B. Tanner (1 shared paper)Stephen J. Asztalos (1 shared paper)Leanne Duffy (1 shared paper)C. Hagmann (1 shared paper)K. van Bibber (1 shared paper)
- Journals
- Journal of High Energy Physics (266 papers)Physics Letters B (157 papers)The European Physical Journal C (133 papers)Physical Review Letters (107 papers)Physical review. D (73 papers)
- Partner nations
- SwitzerlandFranceUnited States
In The Last Decade
David Yu
836 papers receiving 29.5k citations
David Yu's Hit Papers
Peers
Comparison fields: 5 of 119
- Nuclear and High Energy Physics 33.6k
- Astronomy and Astrophysics 255
- Statistical and Nonlinear Physics 122
- Hardware and Architecture 58
- Artificial Intelligence 136
Countries citing papers authored by David Yu
This map shows the geographic impact of David Yu'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 David Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Yu more than expected).
Fields of papers citing papers by David Yu
This network shows the impact of papers produced by David Yu. 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 David Yu. The network helps show where David Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside David Yu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 899 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Observation of a Centrality-Dependent Dijet Asymmetry in Lead-Lead Collisions at s NN = 2.76 TeV with the ATLAS Detector at the LHC Hit paper breakdown → | 2010 | 526 |
| 2 | Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV Hit paper breakdown → | 2018 | 483 |
| 3 | Observation of Associated Near-Side and Away-Side Long-Range Correlations in s N N = 5.02 TeV Proton-Lead Collisions with the ATLAS Detector Hit paper breakdown → | 2013 | 410 |
| 4 | Improved luminosity determination in pp collisions at $\sqrt {s} = 7\ \mathrm{TeV}$ using the ATLAS detector at the LHC Hit paper breakdown → | 2013 | 405 |
| 5 | Measurement of the azimuthal anisotropy for charged particle production in s N N = 2.76 TeV lead-lead collisions with the ATLAS detector Hit paper breakdown → | 2012 | 385 |
| 6 | Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1 Hit paper breakdown → | 2017 | 365 |
| 7 | Performance of pile-up mitigation techniques for jets in $$pp$$ p p collisions at $$\sqrt{s}=8$$ s = 8 TeV using the ATLAS detector Hit paper breakdown → | 2016 | 362 |
| 8 | Combined measurements of Higgs boson couplings in proton–proton collisions at $$\sqrt{s}=13\,\text {Te}\text {V} $$ Hit paper breakdown → | 2019 | 359 |
| 9 | Extraction and validation of a new set of CMS pythia8 tunes from underlying-event measurements Hit paper breakdown → | 2020 | 299 |
| 10 | 2016 | 274 | |
| 11 | 2012 | 271 | |
| 12 | 2012 | 264 | |
| 13 | 2014 | 259 | |
| 14 | 2012 | 249 | |
| 15 | 2016 | 237 | |
| 16 | 2011 | 236 | |
| 17 | 2018 | 235 | |
| 18 | 2014 | 228 | |
| 19 | Performance of the CMS Level-1 trigger in proton-proton collisions at √s = 13 TeV Hit paper breakdown → | 2020 | 216 |
| 20 | 2019 | 214 |
About David Yu
David Yu is a scholar working on Nuclear and High Energy Physics, Computer Networks and Communications, Artificial Intelligence, Control and Systems Engineering and Information Systems, having authored 899 papers that have together received 34.2k indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (763 papers), High-Energy Particle Collisions Research (102 papers), Particle Detector Development and Performance (51 papers), Quantum Chromodynamics and Particle Interactions (37 papers), Anomaly Detection Techniques and Applications (5 papers), Dark Matter and Cosmic Phenomena (4 papers), Distributed and Parallel Computing Systems (3 papers) and Cloud Computing and Resource Management (2 papers). The work is most often cited by research in Nuclear and High Energy Physics (33.6k citations), Astronomy and Astrophysics (255 citations), Statistical and Nonlinear Physics (122 citations), Hardware and Architecture (58 citations) and Artificial Intelligence (136 citations). David Yu has collaborated with scholars based in Switzerland, France and United States. Frequent co-authors include Leslie J Rosenberg, Richard F. Bradley, P. Sikivie, David B. Tanner, Stephen J. Asztalos, Leanne Duffy, C. Hagmann, K. van Bibber, D. Kinion and Thomas G. Robertazzi. Their work appears in journals such as Journal of High Energy Physics, Physics Letters B, The European Physical Journal C, Physical Review Letters and Physical review. D.
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.