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PreprintCC BY 4.0arXiv

Di-hadron Fragmentation Functions beyond LO

Abstract

In this talk, we discuss the extraction of Dihadron Fragmentation Functions (DiFFs) beyond leading order. In particular, we review the latest extraction by the MAP Collaboration of the Unpolarized Dihadron Fragmentation Functions (DiFFs) from a fit of the 2017 BELLE data for the inclusive π+π- pair production within the same jet in e+e- annihilations. This new extraction improves the perturbative QCD accuracy by including NNLO calculations, relies on Monte Carlo generators only for flavor decomposition, and complements the traditional physics-informed parametrization with a Neural Network extraction. We also discuss the setup for the extraction of the transversely polarized DiFFs, where we revisit the NLO calculation for e+e- annihilation into a transversely polarized quark-antiquark pair, obtaining a result different from the one reported in the literature.

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BibTeX
@misc{polano2026dihadron,
  title = {{Di-hadron Fragmentation Functions beyond LO}},
  author = {Luca Polano and Alessandro Bacchetta and Marco Radici},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.04885},
  eprint = {2609.04885},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.04885},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Di-hadron Fragmentation Functions beyond LO
AU  - Luca Polano
AU  - Alessandro Bacchetta
AU  - Marco Radici
PY  - 2026
DA  - 2026/09/04
PB  - arXiv
DO  - 10.48550/arxiv.2609.04885
UR  - https://arxiv.org/abs/2609.04885
AB  - In this talk, we discuss the extraction of Dihadron Fragmentation Functions (DiFFs) beyond leading order. In particular, we review the latest extraction by the MAP Collaboration of the Unpolarized Dihadron Fragmentation Functions (DiFFs) from a fit of the 2017 BELLE data for the inclusive π^+π^- pair production within the same jet in e^+e^- annihilations. This new extraction improves the perturbative QCD accuracy by including NNLO calculations, relies on Monte Carlo generators only for flavor decomposition, and complements the traditional physics-informed parametrization with a Neural Network extraction. We also discuss the setup for the extraction of the transversely polarized DiFFs, where we revisit the NLO calculation for e^+e^- annihilation into a transversely polarized quark-antiquark pair, obtaining a result different from the one reported in the literature.
ER  -