Next-to-leading power threshold factorization for Drell-Yan production

TL;DR

This paper develops a formalism for calculating next-to-leading power corrections in Drell-Yan production near threshold, introducing new collinear functions and analyzing resummation challenges within soft-collinear effective theory.

Contribution

It introduces the NLP factorization formula for Drell-Yan, defines new collinear functions, and discusses resummation issues at next-to-leading power.

Findings

Derived the one-loop result for NLP collinear functions

Extended leading power factorization to subleading powers

Highlighted challenges in NLP resummation

Abstract

We present the next-to-leading power (NLP) factorization formula for the $q\bar{q}\to \gamma^*+X$ channel of the Drell-Yan production near the kinematic threshold limit. The formalism used for the computation of next-to-leading power corrections within soft-collinear effective field theory is introduced, we discuss the emergence of new objects, the NLP collinear functions, and define them through an operator matching equation. We review the leading power factorization before extending it to subleading powers. We also present the one-loop result for the newly introduced collinear function, and demonstrate explicitly conceptual issues in performing next-to-leading logarithmic resummation at next-to-leading power.