Table of Contents
Fetching ...

On the PB Sudakov: NNLL coefficient, CS kernel and intrinsic-kt

Aleksandra Lelek

TL;DR

This work clarifies how Transverse Momentum Dependent PB evolution reproduces CSS-style Sudakov resummation up to NNLL by introducing a dynamical soft-gluon resolution scale and decomposing the Sudakov into perturbative and non-perturbative parts. It demonstrates that a physical soft coupling $alpha_s^{phys}$ can drive PB to NLL and NNLL accuracy, with explicit relations between PB coefficients and CSS coefficients, and shows that non-perturbative Sudakovs can be extracted from PB via multiple soft-radiation models. The study further compares PB-derived CS kernels with existing phenomenological and lattice results, highlighting sensitivity to radiation modeling and the non-parametric nature of PB extractions. It also emphasizes how neglecting the non-perturbative Sudakov can distort intrinsic-kT and energy dependence, underscoring the importance of NP effects for reliable collider predictions.

Abstract

The Transverse Momentum Dependent (TMD) Parton Branching (PB) method incorporates elements of TMD physics into a Monte Carlo (MC) framework to produce high-energy QCD predictions for collider processes. It derives TMDs from the PB evolution equation - solvable with MC techniques - fits them to data, and then enables their use in MC event generators for QCD predictions. In this article, we describe the relation of the PB Sudakov form factor to the Sudakov factor in the CSS formalism. We discuss both perturbative and non-perturbative components. We present recent developments to include NNLL coefficient in the PB Sudakov. We discuss the CS kernel extractions for different evolution scenarios. We remark the recent studies on intrinsic-kt vs center-of-mass (in)dependence in different approaches and their relation to the non-perturbative Sudakov.

On the PB Sudakov: NNLL coefficient, CS kernel and intrinsic-kt

TL;DR

This work clarifies how Transverse Momentum Dependent PB evolution reproduces CSS-style Sudakov resummation up to NNLL by introducing a dynamical soft-gluon resolution scale and decomposing the Sudakov into perturbative and non-perturbative parts. It demonstrates that a physical soft coupling can drive PB to NLL and NNLL accuracy, with explicit relations between PB coefficients and CSS coefficients, and shows that non-perturbative Sudakovs can be extracted from PB via multiple soft-radiation models. The study further compares PB-derived CS kernels with existing phenomenological and lattice results, highlighting sensitivity to radiation modeling and the non-parametric nature of PB extractions. It also emphasizes how neglecting the non-perturbative Sudakov can distort intrinsic-kT and energy dependence, underscoring the importance of NP effects for reliable collider predictions.

Abstract

The Transverse Momentum Dependent (TMD) Parton Branching (PB) method incorporates elements of TMD physics into a Monte Carlo (MC) framework to produce high-energy QCD predictions for collider processes. It derives TMDs from the PB evolution equation - solvable with MC techniques - fits them to data, and then enables their use in MC event generators for QCD predictions. In this article, we describe the relation of the PB Sudakov form factor to the Sudakov factor in the CSS formalism. We discuss both perturbative and non-perturbative components. We present recent developments to include NNLL coefficient in the PB Sudakov. We discuss the CS kernel extractions for different evolution scenarios. We remark the recent studies on intrinsic-kt vs center-of-mass (in)dependence in different approaches and their relation to the non-perturbative Sudakov.

Paper Structure

This paper contains 5 sections, 2 equations, 2 figures.

Figures (2)

  • Figure 1: The PB iTMDs (left) and TMDs (middle) obtained with NLO, NLL and NNLL evolution for down quark at $100\;\textrm{GeV}$ (and $x=0.001$ for the TMD case). The prediction for $Z$ boson $p_{\bot}$ at $8\;\textrm{TeV}$ (right) obtained with NLO ME matched to the TMDs shown in the middle plot.
  • Figure 2: CS kernels extracted for different PB evolution scenarios, compared to literature examples.