Combining higher-order resummation with multiple NLO calculations and parton showers in GENEVA

By Simone Alioli, Christian W. Bauer, Calvin Berggren, A. Hornig, F. Tackmann, C. Vermilion, Jonathan R. Walsh, Saba Zuberi. 2012

142 citations recorded by the source corpus.

A bstractWe extend the lowest-order matching of tree-level matrix elements with parton showers to give a complete description at the next higher perturbative accuracy in αs at both small and large jet resolutions, which has not been achieved so far. This requires the combination of the higher-order resummation of large Sudakov logarithms at small values of the jet resolution variable with the full next-to-leading-order (NLO) matrix-element corrections at large values. As a by-product, this combination naturally leads to a smooth connection of the NLO calculations for different jet multiplicities. In this paper, we focus on the general construction of our method and discuss its application to e+e− and pp collisions. We present first results of the implementation in the Geneva Monte Carlo framework. We employ N-jettiness as the jet resolution variable, combining its next-to-next-to-leading logarithmic resummation with fully exclusive NLO matrix elements, and Pythia 8 as the backend for further parton showering and hadronization. For hadronic collisions, we take Drell-Yan production as an example to apply our construction. For e+e− → jets, taking αs(mZ) = 0.1135 from fits to LEP thrust data, together with the Pythia 8 hadronization model, we obtain good agreement with LEP data for a variety of 2-jet observables.

Subfields: Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/7280611409519359ea4358a14c00ce6d982808c0

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In Nuclear and High Energy Physics

Citations in the corpus

Les Houches 2015: Physics at TeV Colliders Standard Model Working Group Report (2016, methodology): “0-jettiness resummations within SCET have been considered recently in Drell-Yan production [88] using the Geneva Monte Carlo framework which also matches the results to a parton shower [128].”
The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations (2014, background): “NLO (and beyond) mergings are thus inherently more complicated than LO ones, because LO-matching is basically trivial; they have attracted a significant amount of attention lately [184, 191, 198–207].”
Jet substructure at the Large Hadron Collider: A review of recent advances in theory and machine learning (2017, background): “There has also been significant recent progress in matching specific processes at NNLO [166, 182, 183, 184, 185, 186].”
OpenLoops 2 (2019, methodology): “The OpenLoops program can be used as a plug-in by the Monte Carlo programs Sherpa [26, 47], Powheg-Box [27], Herwig++ [32], Geneva [48], and Whizard [49], which possess built-in interfaces that control all relevant OpenLoops functionalities in a largely automated way, requiring In the following, by ”
N-jettiness subtractions for NNLO QCD calculations (2015, methodology): “[67] for a slightly modified version of TN .”