Ian Moult

2.9k total citations · 1 hit paper
69 papers, 1.8k citations indexed

About

Ian Moult is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Aerospace Engineering. According to data from OpenAlex, Ian Moult has authored 69 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Nuclear and High Energy Physics, 5 papers in Astronomy and Astrophysics and 4 papers in Aerospace Engineering. Recurrent topics in Ian Moult's work include Particle physics theoretical and experimental studies (59 papers), High-Energy Particle Collisions Research (39 papers) and Quantum Chromodynamics and Particle Interactions (38 papers). Ian Moult is often cited by papers focused on Particle physics theoretical and experimental studies (59 papers), High-Energy Particle Collisions Research (39 papers) and Quantum Chromodynamics and Particle Interactions (38 papers). Ian Moult collaborates with scholars based in United States, China and France. Ian Moult's co-authors include Hua Xing Zhu, Iain W. Stewart, Hao Chen, Frank J. Tackmann, Jesse Thaler, Andrew J. Larkoski, Lorena Rothen, Duff Neill, Lance J. Dixon and Xiaoyuan Zhang and has published in prestigious journals such as Physical Review Letters, Applied Physics Letters and Journal of High Energy Physics.

In The Last Decade

Ian Moult

69 papers receiving 1.8k citations

Hit Papers

Conformal collider physics meets LHC data 2025 2026 2025 5 10 15 20
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Conformal collider physics meets LHC data
    2025 20 citations Kyle Lee, Ian Moult et al. Physical review. D profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ian Moult United States 28 1.6k 187 86 82 46 69 1.8k
V. A. Khoze United Kingdom 33 3.0k 1.9× 232 1.2× 70 0.8× 28 0.3× 51 1.1× 130 3.2k
W.-S. Hou Taiwan 32 3.0k 1.8× 340 1.8× 100 1.2× 44 0.5× 67 1.5× 144 3.1k
G. Valencia United States 27 2.5k 1.6× 246 1.3× 83 1.0× 69 0.8× 44 1.0× 132 2.6k
P. Ilten United States 14 2.8k 1.7× 485 2.6× 87 1.0× 211 2.6× 53 1.2× 26 2.9k
Zhong-Bo Kang United States 34 2.8k 1.7× 75 0.4× 50 0.6× 40 0.5× 51 1.1× 121 2.9k
G. Ingelman Sweden 20 2.6k 1.6× 136 0.7× 88 1.0× 21 0.3× 56 1.2× 91 2.6k
W. J. Stirling United Kingdom 29 4.6k 2.8× 334 1.8× 79 0.9× 72 0.9× 75 1.6× 101 4.7k
Hua Xing Zhu China 32 2.5k 1.5× 173 0.9× 56 0.7× 84 1.0× 43 0.9× 78 2.6k
Thomas Becher Switzerland 32 4.1k 2.5× 287 1.5× 102 1.2× 70 0.9× 56 1.2× 67 4.2k
R. S. Thorne United Kingdom 31 5.3k 3.3× 357 1.9× 52 0.6× 74 0.9× 74 1.6× 93 5.4k

Countries citing papers authored by Ian Moult

Since Specialization
Citations

This map shows the geographic impact of Ian Moult'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 Ian Moult with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian Moult more than expected).

Fields of papers citing papers by Ian Moult

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ian Moult. 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 Ian Moult. The network helps show where Ian Moult may publish in the future.

Co-authorship network of co-authors of Ian Moult

This figure shows the co-authorship network connecting the top 25 collaborators of Ian Moult. A scholar is included among the top collaborators of Ian Moult 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 Ian Moult. Ian Moult is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Andrés, Carlota, et al.. (2025). Towards an interpretation of the first measurements of energy correlators in the quark-gluon plasma. Journal of High Energy Physics. 2025(3). 6 indexed citations
2.
Lee, Kyle, et al.. (2025). Small radius inclusive jet production at the LHC through NNLO+NNLL. Journal of High Energy Physics. 2025(8). 1 indexed citations
3.
Schwarz, D., et al.. (2024). Using the W as a standard candle to reach the top. 368–368. 1 indexed citations
4.
Moult, Ian, et al.. (2024). Energy-energy correlations on tracks: factorization and resummation. UvA-DARE (University of Amsterdam). 69–69. 1 indexed citations
5.
Andrés, Carlota, et al.. (2024). Seeing beauty in the quark-gluon plasma with energy correlators. Physical review. D. 110(3). 19 indexed citations
6.
Bossi, Hannah, et al.. (2024). Imaging the wakes of jets with energy-energy-energy correlators. Journal of High Energy Physics. 2024(12). 16 indexed citations
7.
Moult, Ian, et al.. (2024). A collinear perspective on the Regge limit. Journal of High Energy Physics. 2024(5). 8 indexed citations
8.
Chicherin, Dmitry, et al.. (2024). Collinear limit of the four-point energy correlator in N=4 supersymmetric Yang-Mills theory. Physical review. D. 110(9). 13 indexed citations
9.
Bossi, Hannah, et al.. (2024). Imaging the Wake of a Jet with Energy Correlators. 296–296. 1 indexed citations
10.
Li, Hai Tao, et al.. (2024). The transverse energy-energy correlator at next-to-next-to-next-to-leading logarithm. Journal of High Energy Physics. 2024(9). 15 indexed citations
11.
Moult, Ian, et al.. (2024). Precision Top Mass Measurement Using Energy Correlators. Research Explorer (The University of Manchester). 312–312. 1 indexed citations
12.
Andrés, Carlota, et al.. (2023). Resolving the Scales of the Quark-Gluon Plasma with Energy Correlators. Physical Review Letters. 130(26). 262301–262301. 49 indexed citations
13.
Moult, Ian. (2023). Subleading power factorization with radiative functions. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 27 indexed citations
14.
Moult, Ian, et al.. (2023). New paradigm for precision top physics: Weighing the top with energy correlators. Physical review. D. 107(11). 40 indexed citations
15.
Komiske, Patrick, Ian Moult, Jesse Thaler, & Hua Xing Zhu. (2023). Analyzing N-Point Energy Correlators inside Jets with CMS Open Data. Physical Review Letters. 130(5). 70 indexed citations
16.
Chen, Hao, Ian Moult, & Hua Xing Zhu. (2022). Spinning gluons from the QCD light-ray OPE. Journal of High Energy Physics. 2022(8). 38 indexed citations
17.
Moult, Ian, et al.. (2022). Extending Precision Perturbative QCD with Track Functions. Physical Review Letters. 128(18). 182001–182001. 46 indexed citations
18.
Moult, Ian. (2022). First subleading power resummation for event shapes. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 47 indexed citations
19.
Moult, Ian. (2020). Fermionic Glauber operators and quark reggeization. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 14 indexed citations
20.
Rothen, Lorena, Frank J. Tackmann, Ian Moult, Iain W. Stewart, & Hua Xing Zhu. (2017). Subleading power corrections for N-jettiness subtractions. Physical Review Letters. 16 indexed citations

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.

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