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PreprintarXiv licencearXiv

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.

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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  -