Identified Hadron Production at Hadron Colliders in Next-to-Next-to-Leading-Order QCD
Michał Czakon, Terry Generet, Alexander Mitov, Rene Poncelet
TL;DR
This work delivers the first NNLO QCD predictions for identified hadron production at hadron colliders, enabling precision tests of fragmentation-function universality and potential global fits with NNLO FFs. The calculations use a factorized framework with nonperturbative fragmentation functions, employ numerical NNLO massless coefficient functions, and apply STRIPPER subtraction to handle infrared singularities, extending to two-hadron observables. The NNLO corrections reduce scale uncertainties and show good perturbative convergence across observables, though fragmentation-function uncertainties remain the dominant theoretical error. The results indicate the necessity of improved NNLO fragmentation functions to fully exploit NNLO precision in hadron-collider phenomenology and to realize global NNLO FF fits when combined with NNLO SIDIS/SIA data.
Abstract
In this work we calculate for the first time the next-to-next-to leading order (NNLO) QCD corrections to identified hadron production at hadron colliders. The inclusion of the NNLO correction has an important impact on all observables considered in this work. Higher order corrections reduce scale uncertainty and in almost all cases are moderate. Overall, good perturbative convergence is observed across kinematics and observables. The uncertainty due to missing higher orders is relatively small and, in many cases, smaller than the experimental uncertainty. The largest source of theoretical uncertainty at present is from the knowledge of the non-perturbative parton-to-hadron fragmentation functions (FF), which dwarfs the scale uncertainty in most kinematic ranges. The inclusion of NNLO corrections demonstrates the precision studies potential of this class of observables. To fully realize this potential, however, a new generation of improved fragmentation functions may be needed. The results of the present work will enable global fits of FF with NNLO precision.
