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Author

Roy Stegeman

Observed names: STEGEMAN, ROY, Stegeman, R, Stegeman, Roy
Observed institutions: University of Milan, European Physical Society, Technology Innovation Institute, Istituto Nazionale di Fisica Nucleare, Sezione di Milano, University of Jyväskylä, University of Edinburgh
ORCID: 0000-0002-3852-8009
Observed ORCID: 0000-0002-3852-8009
OpenAlex ID: A5024601234
The path to proton structure at 1% accuracy
2022 · Richard D. Ball, Stefano Carrazza, et al. · The European Physical Journal C · 660
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Machine learning and LHC event generation
2023 · Anja Butter, Tilman Plehn, et al. · SciPost Physics · 198
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An open-source machine learning framework for global analyses of parton distributions
2021 · Richard D. Ball, Stefano Carrazza, et al. · The European Physical Journal C · 122
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The path to $$\hbox {N}^3\hbox {LO}$$ parton distributions
2024 · Richard D. Ball, Andrea Barontini, et al. · The European Physical Journal C · 99
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Determination of the theory uncertainties from missing higher orders on NNLO parton distributions with percent accuracy
2024 · Richard D. Ball, Andrea Barontini, et al. · The European Physical Journal C · 68
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Neutrino structure functions from GeV to EeV energies
2023 · Alessandro Candido, Alfonso Garcia, et al. · Journal of High Energy Physics · 64
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Intrinsic charm quark valence distribution of the proton
2024 · Richard D. Ball, Alessandro Candido, et al. · Physical review. D/Physical review. D. · 53
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Photons in the proton: implications for the LHC
2024 · Richard D. Ball, Andrea Barontini, et al. · The European Physical Journal C · 51
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Yadism: yet another deep-inelastic scattering module
2024 · Alessandro Candido, Felix Hekhorn, et al. · The European Physical Journal C · 36
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Combination of aN3LO PDFs and implications for Higgs production cross-sections at the LHC
2025 · Thomas Cridge, Lucian A Harland-Lang, et al. · Journal of Physics G Nuclear and Particle Physics · 29
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Correlation and combination of sets of parton distributions
2021 · Richard D. Ball, Stefano Forte, et al. · The European Physical Journal C · 23
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Gravitational D-form factor: the σ-meson as a dilaton confronted with lattice QCD data I
2026 · Roy Stegeman, Roman Zwicky · Journal of High Energy Physics · 21
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A determination of $$\alpha _s(m_Z)$$ at $${{\textrm{aN}}}^3{{\textrm{LO}}}_{{\textrm{QCD}}}\otimes {{\textrm{NLO}}}_{{\textrm{QED}}}$$ accuracy from a global PDF analysis
2025 · Richard D. Ball, Andrea Barontini, et al. · The European Physical Journal C · 19
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A data-based parametrization of parton distribution functions
2022 · Stefano Carrazza, Juan Cruz-Martinez, et al. · The European Physical Journal C · 19
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Gluon gravitational D-form factor: the σ-meson as a dilaton confronted with lattice data II
2026 · Roy Stegeman, Roman Zwicky · Journal of High Energy Physics · 18
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An FONLL prescription with coexisting flavor number PDFs
2024 · Andrea Barontini, Alessandro Candido, et al. · Journal of High Energy Physics · 18
Parton distributions confront LHC Run II data: a quantitative appraisal
2025 · Amedeo Chiefa, Mark N. Costantini, et al. · Journal of High Energy Physics · 16
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Heavy quarks in polarised deep-inelastic scattering at the electron-ion collider
2024 · Felix Hekhorn, Giacomo Magni, et al. · The European Physical Journal C · 16
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Hyperparameter optimisation in deep learning from ensemble methods: applications to proton structure
2025 · Juan Cruz-Martinez, Aron Jansen, et al. · Machine Learning Science and Technology · 12
Parton distributions with higher twist and jet power corrections
2026 · Richard D. Ball, Amedeo Chiefa, et al. · The European Physical Journal C · 7
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A determination of the top mass from a global PDF analysis
2026 · Richard D. Ball, Jaco ter Hoeve, et al. · Journal of High Energy Physics · 4
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Extractions of the strong coupling from collider data without PDF refitting are biased
2025 · Forte, Stefano, Rojo, Juan, et al. · VU Research Portal · 4
Parton distribution functions and theory parameters: an NNPDF perspective
2026 · Ball, Richard D., Giani, Tommaso, et al. · arXiv (Cornell University) · 2
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Studying the parton content of the proton with deep learning models
2020 · Juan Manuel Cruz Martinez, Stefano Carrazza, et al. · Artificial Intelligence for Science, Industry and Society (AISIS) · 2
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Extractions of the strong coupling from collider data without PDF refitting are biased
2026 · Roy Stegeman, Stefano Forte, et al. · European Physical Society Conference on High Energy Physics (EPS-HEP) · 1
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Works count: 44
Citation count: 1,632
H-index: 17
I10-index: 22
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