First next-to-next-to-leading-order extraction of fragmentation functions for Lambda hyperons
Abstract
We present MAPFF1.0_Lambda, the first global analysis at next-to-next-to-leading order in perturbative QCD of the collinear unpolarised fragmentation functions of Lambda hyperons. The fit is based on data from single-inclusive electron-positron annihilation, and from both neutral-current and -- for the first time -- charged-current semi-inclusive deep-inelastic scattering. We have adopted a statistical framework based on Monte Carlo sampling and parametrised fragmentation functions in terms of a neural network. The fragmentation function set comprises a total of seven independent parton flavours, allowing for the first independent determination of valence-quark distributions. Our analysis offers new insights into the hadronisation mechanism of strange baryons and establishes a baseline for future phenomenological and experimental investigations.
Versions
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BibTeX
@misc{bertone2026first,
title = {{First next-to-next-to-leading-order extraction of fragmentation functions for Lambda hyperons}},
author = {Valerio Bertone and Alessia Bongallino and Amedeo Chiefa and Miguel G. Echevarria and Gunar Schnell},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2605.05314},
eprint = {2605.05314},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2605.05314},
}
RIS
TY - UNPB
TI - First next-to-next-to-leading-order extraction of fragmentation functions for Lambda hyperons
AU - Valerio Bertone
AU - Alessia Bongallino
AU - Amedeo Chiefa
AU - Miguel G. Echevarria
AU - Gunar Schnell
PY - 2026
DA - 2026/10/13
PB - arXiv
DO - 10.48550/arxiv.2605.05314
UR - https://arxiv.org/abs/2605.05314
AB - We present MAPFF1.0_Lambda, the first global analysis at next-to-next-to-leading order in perturbative QCD of the collinear unpolarised fragmentation functions of Lambda hyperons. The fit is based on data from single-inclusive electron-positron annihilation, and from both neutral-current and -- for the first time -- charged-current semi-inclusive deep-inelastic scattering. We have adopted a statistical framework based on Monte Carlo sampling and parametrised fragmentation functions in terms of a neural network. The fragmentation function set comprises a total of seven independent parton flavours, allowing for the first independent determination of valence-quark distributions. Our analysis offers new insights into the hadronisation mechanism of strange baryons and establishes a baseline for future phenomenological and experimental investigations.
ER -