Publications
My work in experimental particle physics has contributed to a wide range of publications — from precision measurements within the ATLAS Collaboration to method-oriented studies on machine learning and anomaly detection. These papers reflect the diversity of my research, spanning collider phenomenology, event reconstruction, and statistical modeling.
As a member of the ATLAS Collaboration, I have co-authored over 600 publications, while contributing directly to a focused set of key analyses, particularly in top-quark physics, event reconstruction, and searches for new physics. Beyond ATLAS, I have published multiple independent projects on machine learning and data analysis techniques in high-energy physics.
📚 Complete publication list available via: Google Scholar | InspireHEP | ORCID.
ATLAS Publications
These papers are part of my collaborative work within the ATLAS experiment at CERN. While many are large-scale efforts, I’ve made substantial personal contributions to several key publications — especially those tied to my research on rare top-quark processes and searches for new physics signatures.
Observation of tt̄ Threshold Enhancement
Authors: ATLAS Collaboration.
Title: Observation of a cross-section enhancement near the tt̅ production threshold in √s = 13 TeV pp collisions with the ATLAS detector.
ATLAS-CONF-2025-008 (Jul 2025).
Dijet Anomaly Detection with ATLAS
Authors: ATLAS Collaboration (Georges Aad, …, Knut Zoch, …, and Lukasz Zwalinski).
Title: Weakly supervised anomaly detection for resonant new physics in the dijet final state using proton-proton collisions at √s = 13 TeV with the ATLAS detector.
Reference: Submitted to Phys. Rev. D.
arXiv:2502.09770 (Feb 2025).
tt̄ + charm Production Measurement
Authors: ATLAS Collaboration (Georges Aad, …, Knut Zoch, …, and Lukasz Zwalinski).
Title: Measurement of top-quark pair production in association with charm quarks in proton-proton collisions at √s = 13 TeV with the ATLAS detector.
Reference: Phys. Lett. B 860 (2025) 139177.
DOI:10.1016/j.physletb.2024.139177 |
arXiv:2409.11305.
Top+X Roadmap for Run 3 and beyond
Authors: ATLAS Collaboration.
Title: Roadmap towards future combinations and Effective Field Theory interpretations of top+X processes.
ATL-PHYS-PUB-2023-030 (Sep 2023).
tt̅ɣ and tWɣ Precision Measurements in the eμ Channel
Authors: ATLAS Collaboration (Georges Aad, …, Knut Zoch, …, and Lukasz Zwalinski).
Title: Measurements of inclusive and differential cross‐sections of combined tt̅ɣ and tWɣ production in the eμ channel at 13 TeV with the ATLAS detector.
Reference: JHEP 09 (2020) 049.
DOI:10.1007/JHEP09(2020)049 |
arXiv:2007.06946.
tt̅ɣ Production in 1L and 2L Final States
Authors: ATLAS Collaboration (Georges Aad, …, Knut Zoch, …, and Lukasz Zwalinski).
Title: Measurements of inclusive and differential fiducial cross-sections of tt̅ɣ production in leptonic final states at √s = 13 TeV in ATLAS.
Reference: Eur. Phys. J. C 79 (2019) 382.
DOI:10.1140/epjc/s10052-019-6849-6 |
arXiv:1812.01697.
tt̅Z and tt̅W Cross-Sections in Run 2
Authors: ATLAS Collaboration (Morad Aaboud, …, Knut Zoch, …, and Lukasz Zwalinski).
Title: Measurement of the tt̅Z and tt̅W cross sections in proton–proton collisions at √s = 13 TeV with the ATLAS detector.
Reference: Phys. Rev. D 99 (2019) 072009.
DOI:10.1103/PhysRevD.99.072009 |
arXiv:1901.03584.
Independent and Methodological Work
This section features peer-reviewed publications and open resources I’ve led or co-led outside the ATLAS collaboration. These projects focus on machine learning, event reconstruction, open datasets, and anomaly detection, bridging physics with broader computational challenges.
RODEM Jet Datasets for Machine Learning
Authors: Knut Zoch, John Andrew Raine, Debajyoti Sengupta, and Tobias Golling.
Title: RODEM Jet Datasets.
arXiv:2408.11616 (Aug 2024).
PC-JeDi: Particle Cloud Jet Diffusion
Authors: Matthew Leigh, Debajyoti Sengupta, Guillaume Quétant, John Andrew Raine, Knut Zoch, and Tobias Golling.
Title: PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics.
Reference: SciPost Phys. 16 (2024) 018.
DOI:10.21468/SciPostPhys.16.1.018 |
arXiv:2303.05376.
ν²-Flows: Multi-Neutrino Reconstruction
Authors: John Andrew Raine, Matthew Leigh, Knut Zoch, and Tobias Golling.
Title: ν²-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows.
Reference: Phys. Rev. D 109 (2024) 012005.
DOI:10.1103/PhysRevD.109.012005 |
arXiv:2307.02405.
Topographs: Graph Neural Networks for Event Reconstruction
Authors: Lukas Ehrke, John Andrew Raine, Knut Zoch, Manuel Guth, and Tobias Golling.
Title: Topological Reconstruction of Particle Physics Processes using Graph Neural Networks.
Reference: Phys. Rev. D 107 (2023) 116019.
DOI:10.1103/PhysRevD.107.116019 |
arXiv:2303.13937.
ν‐Flows: Neutrino Regression with Normalizing Flows
Authors: Matthew Leigh, John Andrew Raine, Knut Zoch, and Tobias Golling.
Title: ν‐Flows: conditional neutrino regression.
Reference: SciPost Phys. 14 (2023) 159.
DOI:10.21468/SciPostPhys.14.6.159 |
arXiv:2207.00664.
These publications illustrate the range and impact of my research — from high-precision collider measurements to innovative methodological work. For context on how these efforts fit into my broader program, see the Research page.
Interested in collaboration or have questions about a specific paper? Feel free to get in touch.