activity
20112026
most citedThe Path to Proton Structure at One-Percent Accuracy

429 citations · 1k across the 33 of their papers we have counts for

collaborators

36 papers

hep-ph2026

PineAPPLv1: fast and flexible theory predictions for present and future colliders

Tomáš Ježo, Emanuele R. Nocera, Tanjona R. Rabemananjara +3

We present PineAPPLv1, a library designed to provide accurate and flexible interpolation tables of partonic cross sections that can be convolved with parton distribution functions…

hep-ph2025★ 1 cited

MATRIX HAWAII: PineAPPL interpolation grids with MATRIX

S. Devoto, T. Jezo, S. Kallweit +1

We present an interface between PineAPPL and Matrix, which allows fully differential cross sections to be calculated in the form of interpolation grids, accurate at next-to-next-to…

hep-ph2025

Fast interpolation grids for the Drell-Yan process

Juan Cruz-Martinez, Alexander Huss, Christopher Schwan

Modern analyses of experimental data from hadron colliders rely on theory predictions at high orders in perturbation theory and a variety of input settings. Interpolation grids fac…

hep-ph2024★ 1 cited

Double-pole approximation for leading-order semi-leptonic vector-boson scattering at the LHC

Ansgar Denner, Daniele Lombardi, Christopher Schwan

Measuring vector-boson scattering beyond the fully-leptonic final state is becoming possible at the LHC, which demands to have a solid control on the theory predictions for all fin…

hep-ph2024

Full and approximated NLO predictions for like-sign W-boson scattering at the LHC

Stefan Dittmaier, Christopher Schwan, Ramon Winterhalder

We report on a recent calculation of next-to-leading-order (NLO) QCD and electroweak corrections to like-sign W-boson scattering at the Large Hadron Collider, including all partoni…

hep-ph2024★ 2 cited

The Path to NLO Parton Distributions

The NNPDF Collaboration, Richard D. Ball, Andrea Barontini +16

We extend the existing leading (LO), next-to-leading (NLO), and next-to-next-to-leading order (NNLO) NNPDF4.0 sets of parton distribution functions (PDFs) to approximate next-to-ne…