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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.12013 |
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| _version_ | 1866929286927089664 |
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| author | Dall'Olio, P. De Soto, F. Mezrag, C. Chávez, J. M. Morgado Moutarde, H. Rodríguez-Quintero, J. Sznajder, P. Segovia, J. |
| author_facet | Dall'Olio, P. De Soto, F. Mezrag, C. Chávez, J. M. Morgado Moutarde, H. Rodríguez-Quintero, J. Sznajder, P. Segovia, J. |
| contents | Relying on the polynomiality property of generalized parton distributions, which roots on Lorentz covariance, we prove that it is enough to know them at vanishing- and low-skewness within the DGLAP region to obtain a unique extension to their entire support up to a D-term. We put this idea in practice using two methods: Reconstruction using artificial neural networks and finite-elements methods. We benchmark our results against standard models for generalized parton distributions. In agreement with the formal expectation, we obtain a very accurate reconstructions for a maximal value of the skewness as low as 20% of the longitudinal momentum fraction. This result might be relevant for reconstruction of generalized parton distribution from experimental and lattice QCD data, where computations are for now, restricted in skewness. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_12013 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Unraveling Generalized Parton Distributions Through Lorentz Symmetry and Partial DGLAP Knowledge Dall'Olio, P. De Soto, F. Mezrag, C. Chávez, J. M. Morgado Moutarde, H. Rodríguez-Quintero, J. Sznajder, P. Segovia, J. High Energy Physics - Phenomenology Nuclear Theory Relying on the polynomiality property of generalized parton distributions, which roots on Lorentz covariance, we prove that it is enough to know them at vanishing- and low-skewness within the DGLAP region to obtain a unique extension to their entire support up to a D-term. We put this idea in practice using two methods: Reconstruction using artificial neural networks and finite-elements methods. We benchmark our results against standard models for generalized parton distributions. In agreement with the formal expectation, we obtain a very accurate reconstructions for a maximal value of the skewness as low as 20% of the longitudinal momentum fraction. This result might be relevant for reconstruction of generalized parton distribution from experimental and lattice QCD data, where computations are for now, restricted in skewness. |
| title | Unraveling Generalized Parton Distributions Through Lorentz Symmetry and Partial DGLAP Knowledge |
| topic | High Energy Physics - Phenomenology Nuclear Theory |
| url | https://arxiv.org/abs/2401.12013 |