Multi-jet Merging with NLO Matrix Elements

Abstract

In the algorithm presented here, the ME+PS approach to merge samples of tree-level matrix elements into inclusive event samples is combined with the POWHEG method, which includes exact next-to-leading order matrix elements in the parton shower. The advantages of the method are discussed and the quality of its implementation in SHERPA is exemplified by results for e{sup +}e{sup -} annihilation into hadrons at LEP, for deep-inelastic lepton-nucleon scattering at HERA, for Drell-Yan lepton-pair production at the Tevatron and for W{sup +}W{sup -}-production at LHC energies. The simulation of hard QCD radiation in parton-shower Monte Carlos has seen tremendous progress over the last years. It was largely stimulated by the need for more precise predictions at LHC energies where the large available phase space allows additional hard QCD radiation alongside known Standard Model processes or even signals from new physics. Two types of algorithms have been developed, which allow to improve upon the soft-collinear approximations made in the parton shower, such that hard radiation is simulated according to exact matrix elements. In the ME+PS approach [1] higher-order tree-level matrix elements for different final-state jet multiplicity are merged with each other and with subsequent parton shower emissions to generate an inclusive sample. Such a prescription is invaluable for analyses which are sensitive to final states with a large jet multiplicity. The only remaining deficiency of such tree-level calculations is the large uncertainty stemming from scale variations. The POWHEG method [2] solves this problem for the lowest multiplicity subprocess by combining full NLO matrix elements with the parton shower. While this leads to NLO accuracy in the inclusive cross section and the exact radiation pattern for the first emission, it fails to describe higher-order emissions with improved accuracy. Thus it is not sufficient if final states with high jet multiplicities are considered. With the complementary advantages of these two approaches, the question arises naturally whether it would be possible to combine them into an even more powerful one. Such a combined algorithm was independently developed in [5] and [6]. Here a summary of the algorithm is given and predictions from corresponding Monte-Carlo predictions are presented.