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Author  |
Martinez de Lejarza, J.J.; Wu, H.Y.; Kyriienko, O.; Rodrigo, G.; Grossi, M. |
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Title |
Quantum Chebyshev probabilistic models for fragmentation functions |
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Journal Article |
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Year |
2025 |
Publication |
Communications Physics |
Abbreviated Journal |
Commun. Phys. |
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Volume |
8 |
Issue |
1 |
Pages |
448 - 9pp |
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Abstract |
Quantum generative modeling is emerging as a powerful tool for advancing data analysis in high-energy physics, where complex multivariate distributions are common. However, efficiently learning and sampling these distributions remains challenging. We propose a quantum protocol for a bivariate probabilistic model based on shifted Chebyshev polynomials, trained as a circuit-based representation of two correlated variables, with sampling performed via quantum Chebyshev transforms. As a key application, we study fragmentation functions (FFs) of charged pions and kaons from single-inclusive hadron production in electron-positron annihilation. We learn the joint distribution of momentum fraction z and energy scale Q, and infer their correlations from the entanglement structure. Building on the generalization capabilities of the quantum model and extended register architecture, we perform fine-grid multivariate sampling for FF dataset augmentation. Our results highlight the growing potential of quantum generative modeling to advance data analysis and scientific discovery in high-energy physics. |
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Address |
[Martinez de Lejarza, Jorge J.; Rodrigo, German] Univ Valencia, CSIC, Inst Fis Corpuscular, Parc Cientif, Valencia, Spain, Email: jormard@ific.uv.es |
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Publisher |
Nature Portfolio |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2399-3650 |
ISBN |
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Notes |
WOS:001618164000008 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
6942 |
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