An extraction of the Collins-Soper kernel from a joint analysis of experimental and lattice data

Fuente: arXiv
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Main Authors: Avkhadiev, Artur, Bertone, Valerio, Bissolotti, Chiara, Cerutti, Matteo, Fu, Yang, Rodini, Simone, Shanahan, Phiala, Wagman, Michael, Zhao, Yong
Format: Preprint
Published: 2025
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author Avkhadiev, Artur
Bertone, Valerio
Bissolotti, Chiara
Cerutti, Matteo
Fu, Yang
Rodini, Simone
Shanahan, Phiala
Wagman, Michael
Zhao, Yong
author_facet Avkhadiev, Artur
Bertone, Valerio
Bissolotti, Chiara
Cerutti, Matteo
Fu, Yang
Rodini, Simone
Shanahan, Phiala
Wagman, Michael
Zhao, Yong
contents We present a first joint extraction of the Collins-Soper kernel (CSK) combining experimental and lattice QCD data in the context of an analysis of transverse-momentum-dependent distributions (TMDs). Based on a neural-network parametrization, we perform a Bayesian reweighting of an existing fits of TMDs using lattice data, as well as a joint TMD fit to lattice and experimental data. We consistently find that the inclusion of lattice information shifts the central value of the CSK by approximately 10% and reduces its uncertainty by 40-50%, highlighting the potential of lattice inputs to improve TMD extractions.
format Preprint
id arxiv_https___arxiv_org_abs_2510_26489
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An extraction of the Collins-Soper kernel from a joint analysis of experimental and lattice data
Avkhadiev, Artur
Bertone, Valerio
Bissolotti, Chiara
Cerutti, Matteo
Fu, Yang
Rodini, Simone
Shanahan, Phiala
Wagman, Michael
Zhao, Yong
High Energy Physics - Phenomenology
High Energy Physics - Experiment
High Energy Physics - Lattice
We present a first joint extraction of the Collins-Soper kernel (CSK) combining experimental and lattice QCD data in the context of an analysis of transverse-momentum-dependent distributions (TMDs). Based on a neural-network parametrization, we perform a Bayesian reweighting of an existing fits of TMDs using lattice data, as well as a joint TMD fit to lattice and experimental data. We consistently find that the inclusion of lattice information shifts the central value of the CSK by approximately 10% and reduces its uncertainty by 40-50%, highlighting the potential of lattice inputs to improve TMD extractions.
title An extraction of the Collins-Soper kernel from a joint analysis of experimental and lattice data
topic High Energy Physics - Phenomenology
High Energy Physics - Experiment
High Energy Physics - Lattice
url https://arxiv.org/abs/2510.26489