Four-loop non-singlet splitting functions in QCD are computed analytically for the first time, with numerical representations provided.
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2026 10verdicts
UNVERDICTED 10representative citing papers
Completes soft-operator formulation for thrust-axis TMD in e+e- and SIDIS, proposes nonperturbative model with event-shape dependence, resums logs, and validates against Pythia8.3 simulations.
Introduces Centauric 1-jettiness in DIS, derives N3LL resummation matched to NLO, and establishes universal non-perturbative power corrections scaling as 1/R via reduction to rescaled hemisphere soft function.
The Collins-Soper kernel is extracted from lattice computations of a vacuum soft function, showing rapidity dependence consistent with Collins-Soper evolution, comparable errors to hadronic methods, and saturation at large transverse separations.
Four-loop non-singlet QCD splitting functions are verified for consistency and used to finalize analytical forms for the gluon virtual anomalous dimension and N^4LL threshold resummation coefficients, revealing a new small-x logarithmic structure.
Defines an IRC-safe one-point charge correlator in DIS, relates it to a new nucleon charge correlator in the forward limit and to TMDs in the back-to-back limit, with SCET derivations verified in QCD to O(alpha_s^2) and resummations to NLL/N3LL.
A lightcone-expansion strategy using Wilson-line correlators and the Method of Regions yields the three-loop soft anomalous dimension for QCD amplitudes with one massive colored particle and arbitrary massless ones.
An AI-assisted Bayesian framework extracts TMD PDFs from global Drell-Yan data using surrogate models for scalable MCMC sampling.
Derives NLO splitting functions and anomalous dimensions for PDFs in alternative factorization schemes and interprets their leading x-behavior as a modified effective evolution scale.
Explicit three-loop computation of negative geometries for F(g,z) with all-loop resummation of one-cycle diagrams and extraction of the cusp anomalous dimension via z-integration.
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AI-assisted modeling and Bayesian inference of unpolarized quark transverse momentum distributions from Drell-Yan data
An AI-assisted Bayesian framework extracts TMD PDFs from global Drell-Yan data using surrogate models for scalable MCMC sampling.