RT Journal Article
T1 Information entropy and fragmentation functions
A1 Benito-Calviño, Guillermo
A1 García-Olivares, Javier
A1 Llanes Estrada, Felipe José
AB Several groups have recently investigated the flow of information in high-energy collisions, from the entanglement entropy of the proton yielding classical Shannon entropy of its parton distribution functions (pdfs), through jet splitting generating entropy, to the entropy distribution in hadron decays.Lacking in the literature is a discussion of the information entropy of fragmentation functions (FFs) in the instances where they can be considered as probability distributions, and we here provide it. We find that this entropy is a single, convenient number to characterize future progress in the extraction of fragmentation functions.We also deploy the related Kullback-Leibler divergence between two distributions to assess existing relations among FFs and parton distribution functions (pdfs) such as that of Barone, Drago and Ma. From a couple of current parametrizations of FFs, we do not find supporting empirical evidence for the relation, although it is possible that FFs and pdfs have similar power-laws near the  x = 1  endpoint.
PB Elsevier
SN 0375-9474
YR 2023
FD 2023-08
LK https://hdl.handle.net/20.500.14352/102827
UL https://hdl.handle.net/20.500.14352/102827
LA eng
NO Benito-Calviño, G., García-Olivares, J., & Llanes-Estrada, F. J. (2023). Information entropy and fragmentation functions. Nuclear Physics A, 1036, 122670.
NO 2023 Acuerdos transformativos CRUE
NO Unión Europea. H2020
NO Ministerio de Ciencia e Innovación (España)
NO Universidad Complutense de Madrid
DS Docta Complutense
RD 9 abr 2025