4.7 Article

Precision predictions for exotic lepton production at the Large Hadron Collider

期刊

PHYSICAL REVIEW D
卷 107, 期 7, 页码 -

出版社

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevD.107.075011

关键词

-

向作者/读者索取更多资源

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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据