Large-x resummation of off-diagonal deep-inelastic parton scattering from d-dimensional refactorization
Martin Beneke, Mathias Garny, Sebastian Jaskiewicz, Robert Szafron,, Leonardo Vernazza, Jian Wang

TL;DR
This paper develops a novel resummation method for off-diagonal deep-inelastic scattering channels near threshold, overcoming divergence issues and deriving new all-order expressions for splitting functions using effective theory techniques.
Contribution
It introduces a $d$-dimensional consistency approach to resum NLP double logarithms in off-diagonal channels, deriving the DGLAP kernel from algebraic all-order formulas.
Findings
Resummation of off-diagonal channels achieved at leading logarithmic order.
Derived DGLAP kernel series involving Bernoulli numbers.
Identified two-scale nature of off-diagonal splitting functions and Sudakov logs.
Abstract
The off-diagonal parton-scattering channels and in deep-inelastic scattering are power-suppressed near threshold . We address the next-to-leading power (NLP) resummation of large double logarithms of to all orders in the strong coupling, which are present even in the off-diagonal DGLAP splitting kernels. The appearance of divergent convolutions prevents the application of factorization methods known from leading power resummation. Employing -dimensional consistency relations from requiring pole cancellations in dimensional regularization between momentum regions, we show that the resummation of the off-diagonal parton-scattering channels at the leading logarithmic order can be bootstrapped from the recently conjectured exponentiation of NLP soft-quark Sudakov logarithms. In particular, we derive a result for the DGLAP kernel in terms…
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