Leading-logarithmic threshold resummation of Higgs production in gluon fusion at next-to-leading power

TL;DR

This paper develops a leading-logarithmic threshold resummation for Higgs production in gluon fusion at next-to-leading power using SCET. The authors derive a factorization formula at NLP, identify the relevant hard, soft, and collinear functions, and perform RG-based resummation, revealing a DY-like structure with C_F replaced by C_A. Their fixed-order expansion agrees with known results and extends to higher orders, while their numerical study at the LHC shows NLP NLP corrections can be sizable and crucial for matching high-precision predictions. The findings highlight the importance of NLP resummation for accurate Higgs phenomenology and motivate advancing to NLL NLP and combining with fixed-order results.

Abstract

We sum the leading logarithms $α_s^n \ln^{2 n-1}(1-z)$, n=1,2,... near the kinematic threshold $z=m_H^2/\hat{s}\to 1$ at next-to-leading power in the expansion in (1-z) for Higgs production in gluon fusion. We highlight the new contributions compared to Drell-Yan production in quark-antiquark annihilation and show that the final result can be obtained to all orders by the substitution of the colour factor $C_F\to C_A$, confirming previous fixed-order results and conjectures. We also provide a numerical analysis of the next-to-leading power leading logarithms, which indicates that they are numerically relevant.

Figures (2)

• Figure 1: Dependence of the NNLL LP and LL NLP resummed Higgs production cross section on the soft scale $\mu_s$, for $\mu_h^2 = m_H^2$. For NLP we present the result for the two cases defined in \ref{['initialconditions']}.
• Figure 2: Same as figure \ref{['sigmamus']}, however using $\mu_h^2 = -m_H^2$ for the hard scale.