Automation of NLO QCD and EW corrections with Sherpa and Recola
This publication presents the combination of the one-loop matrix-element generator Recola with the multipurpose Monte Carlo program Sherpa. Since both programs are highly automated, the resulting Sherpa +Recola framework allows for the computation of - in principle - any Standard Model process at bo...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
24 July 2017
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| In: |
The European physical journal. C, Particles and fields
Year: 2017, Volume: 77, Issue: 7 |
| ISSN: | 1434-6052 |
| DOI: | 10.1140/epjc/s10052-017-5054-8 |
| Online Access: | Verlag, kostenfrei, Volltext: http://dx.doi.org/10.1140/epjc/s10052-017-5054-8 Verlag, kostenfrei, Volltext: https://link.springer.com/article/10.1140/epjc/s10052-017-5054-8 
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| Author Notes: | Benedikt Biedermann, Stephan Bräuer, Ansgar Denner, Mathieu Pellen, Steffen Schumann, Jennifer M. Thompson |
| Summary: | This publication presents the combination of the one-loop matrix-element generator Recola with the multipurpose Monte Carlo program Sherpa. Since both programs are highly automated, the resulting Sherpa +Recola framework allows for the computation of - in principle - any Standard Model process at both NLO QCD and EW accuracy. To illustrate this, three representative LHC processes have been computed at NLO QCD and EW: vector-boson production in association with jets, off-shell ZZ\mathrm{Z}-boson pair production, and the production of a top-quark pair in association with a Higgs boson. In addition to fixed-order computations, when considering QCD corrections, all functionalities of Sherpa, i.e. particle decays, QCD parton showers, hadronisation, underlying events, etc. can be used in combination with Recola. This is demonstrated by the merging and matching of one-loop QCD matrix elements for Drell-Yan production in association with jets to the parton shower. The implementation is fully automatised, thus making it a perfect tool for both experimentalists and theorists who want to use state-of-the-art predictions at NLO accuracy. |
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| Item Description: | Gesehen am 27.06.2018 |
| Physical Description: | Online Resource |
| ISSN: | 1434-6052 |
| DOI: | 10.1140/epjc/s10052-017-5054-8 |