arXiv subjects

Luca Polano

Publications and source records attributed to Luca Polano.

2 recordsLinked to original sources

arXiv2026

Di-hadron Fragmentation Functions beyond LO

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 $\pi^+\pi^-$ 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.

hep-ph↗

arXiv2025

Extraction of Dihadron Fragmentation Functions at NNLO with and without Neural Networks

We present a new extraction of unpolarized Dihadron Fragmentation Functions, which describe the probability density for an unpolarized parton to fragment into a $\pi^+ \pi^-$ pair. Our analysis is based on data from the BELLE collaboration. We improve on previous determinations in several key aspects: we employ state-of-the-art perturbative QCD calculations up to next-to-next-to-leading order (NNLO); we limit the use of Monte Carlo event generators to estimating the relative contributions of different flavors, a necessary input due to the limited flavor sensitivity of the available data; and, in addition to a traditional fit based on a physics-informed functional form, we explore a Neural Network parametrization. This latter approach paves the way for more robust and flexible determinations of Dihadron Fragmentation Functions using machine learning techniques.

hep-ph↗