4.7 Article

Precision predictions for exotic lepton production at the Large Hadron Collider

Journal

PHYSICAL REVIEW D
Volume 107, Issue 7, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevD.107.075011

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This study calculates the total and differential cross sections for the pair production of exotic leptons that could exist in models with vectorlike leptons and in type-III seesaw scenarios at the Large Hadron Collider. The predictions take into account next-to-leading-order QCD corrections and are matched with either parton showers or threshold resummation at the next-to-next-to-leading logarithmic accuracy. The results show an important increase in the cross sections, distortion of the shapes for various differential distributions, and a significant reduction of the scale uncertainties. These predictions are obtained using new FeynRules model implementations and associated Universal FeynRules Output model libraries, completing the set of publicly available next-to-leading-order implementations of new physics models featuring extra leptons in the FeynRules model database.
We calculate total and differential cross sections for the pair production, at the Large Hadron Collider, of exotic leptons that could emerge from models with vectorlike leptons and in type-III seesaw scenarios. Our predictions include next-to-leading-order QCD corrections, and we subsequently match them with either parton showers, or threshold resummation at the next-to-next-to-leading logarithmic accuracy. Our results show an important increase of the cross sections relative to the leading-order predictions, exhibit a distortion of the shapes for various differential distributions, and feature a significant reduction of the scale uncertainties. Our predictions have been obtained from new FeynRules model implementations and associated Universal FeynRules Output (UFO) model libraries. This completes the set of next-to-leading-order implementations of new physics models featuring extra leptons that are publicly available on the FeynRules model database.

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