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NLO predictions for the production of a spin-two particle at the LHC

Das, Goutam; Degrande, Céline; Hirschi, Valentin; Maltoni, Fabio; Shao, Hua-Sheng

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Authors

Goutam Das

Céline Degrande

Valentin Hirschi

Fabio Maltoni

Hua-Sheng Shao



Abstract

We obtain predictions accurate at the next-to-leading order in QCD for the production of a generic spin-two particle in the most relevant channels at the LHC: production in association with coloured particles (inclusive, one jet, two jets and tt¯), with vector bosons (Z,W±,γ) and with the Higgs boson. We present total and differential cross sections as well as branching ratios as a function of the mass and the collision energy also considering the case of non-universal couplings to standard model particles. We find that the next-to-leading order corrections give rise to sizeable K factors for many channels, in some cases exposing the unitarity-violating behaviour of non-universal couplings scenarios, and in general greatly reduce the theoretical uncertainties. Our predictions are publicly available in the MadGraph5_aMC@NLO framework and can, therefore, be directly used in experimental simulations of spin-two particle production for arbitrary values of the mass and couplings.

Citation

Das, G., Degrande, C., Hirschi, V., Maltoni, F., & Shao, H. (2017). NLO predictions for the production of a spin-two particle at the LHC. Physics Letters B, 770, 507-513. https://doi.org/10.1016/j.physletb.2017.05.007

Journal Article Type Article
Acceptance Date May 2, 2017
Online Publication Date May 8, 2017
Publication Date Jul 10, 2017
Deposit Date Jul 28, 2017
Publicly Available Date Jul 28, 2017
Journal Physics Letters B
Print ISSN 0370-2693
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 770
Pages 507-513
DOI https://doi.org/10.1016/j.physletb.2017.05.007
Public URL https://durham-repository.worktribe.com/output/1372242

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Published Journal Article (608 Kb)
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
© 2017 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3






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