Factorization and N^3LL_p+NNLO Predictions for the Higgs Cross Section with a Jet Veto

TL;DR

This paper develops a precise theoretical framework for predicting Higgs boson production cross sections with a jet veto, incorporating advanced resummation techniques and two-loop calculations to improve accuracy.

Contribution

It derives a factorization formula at two-loop accuracy for Higgs production with a jet veto, including the R-dependence and numerical extraction of two-loop beam functions, advancing precision predictions.

Findings

Confirmed the two-loop dependence on jet-radius R.

Demonstrated no leading-power factorization-breaking effects for R=O(1).

Provided detailed numerical predictions at N^3LL_p+NNLO accuracy.

Abstract

We have recently derived a factorization formula for the Higgs-boson production cross section in the presence of a jet veto, which allows for a systematic resummation of large Sudakov logarithms of the form alpha_s^n ln^m(p_T^veto/m_H), along with the large virtual corrections known to affect also the total cross section. Here we determine the ingredients entering this formula at two-loop accuracy. Specifically, we compute the dependence on the jet-radius parameter R, which is encoded in the two-loop coefficient of the collinear anomaly, by means of a direct, fully analytic calculation in the framework of soft-collinear effective theory. We confirm the result obtained by Banfi et al. from a related calculation in QCD, and demonstrate that factorization-breaking, soft-collinear mixing effects do not arise at leading power in p_T^veto/m_H, even for R=O(1). In addition, we extract the two-loop collinear beam functions numerically. We present detailed numerical predictions for the jet-veto cross section with partial next-to-next-to-next-to-leading logarithmic accuracy, matched to the next-to-next-to-leading order cross section in fixed-order perturbation theory. The only missing ingredients at this level of accuracy are the three-loop anomaly coefficient and the four-loop cusp anomalous dimension, whose numerical effects we estimate to be small.