Production of Z-bosons in the parton branching method
A. Bermudez Martinez, P. Connor, D. Dominguez Damiani, L. I. Estevez Banos, F. Hautmann, H. Jung, J. Lidrych, M. Schmitz, S. Taheri Monfared, Q. Wang, R. Zlebcik
TL;DR
This work demonstrates that Z-boson production in Drell–Yan processes at the LHC can be described accurately by combining Parton Branching (PB) TMD parton distributions—fitted to inclusive DIS data at NLO—with NLO Drell–Yan calculations via MC@NLO. The PB framework evolves TMDs using angular ordering, Sudakov factors, and a data-driven starting distribution, yielding predictions for $p_{\rm T}$, rapidity, and $\phi^*$ that agree with ATLAS measurements, with scale uncertainties dominating over TMD uncertainties. The study finds very small TMD-related uncertainties (order $\sim$2%) in most regions, while the lowest $p_{\rm T}$ bin shows sensitivity to the intrinsic $k_t$ distribution, underscoring the role of nonperturbative TMD contributions. Predictions for 13 TeV show continued compatibility without parameter tuning, highlighting the PB-TMD approach as a robust, data-constrained method for precise collider phenomenology and potential constraints on nonperturbative TMD physics.
Abstract
Transverse Momentum Dependent (TMD) parton distributions obtained from the Parton Branching (PB) method are combined with next-to-leading-order (NLO) calculations of Drell-Yan (DY) production. We apply the MCatNLO method for the hard process calculation and matching with the PB TMDs. We compute predictions for the transverse momentum, rapidity and $φ^*$ spectra of Z-bosons. We find that the theoretical uncertainties of the predictions are dominated by the renormalization and factorization scale dependence, while the impact of TMD uncertainties is moderate. The theoretical predictions agree well, within uncertainties, with measurements at the Large Hadron Collider (LHC). In particular, we study the region of lowest transverse momenta at the LHC, and comment on its sensitivity to nonperturbative TMD contributions.
