论文标题
来自黑暗部门阵雨的喷气子结构
Jet Substructure from Dark Sector Showers
论文作者
论文摘要
我们检查了对撞机的现象学预测的鲁棒性,这些预测具有类似QCD的特性的黑暗扇区场景。 LHC在LHC上的深色夸克的生产可能会导致各种签名,具体取决于新物理模型的细节。当迅速生产引起Parton淋浴时产生高度多样性的直接深色黑龙,随后衰减到标准模型Hadron时,一个特别具有挑战性的信号结果。最终状态包含其子结构编码其非QCD来源的喷气机。这是超出标准模型动力学的强烈耦合的相对微妙的签名,因此,至关重要的是,分析包含系统误差以说明建模信号时所做的近似值。我们估计了可观察到的规范子结构的理论不确定性,该可观察到的旨在对基础对象的量规结构,两点能量相关器$ e_2^{(β)} $敏感,通过计算重新启动的分析分布与毕望氏数字结果之间的信封。我们探讨了QCD背景的可分离性,因为颜色的数量,颜色数量,风味数量和深色夸克质量各不相同。此外,我们研究了建模黑暗扇形强调固有的不确定性。提供了简单的估计值,这些估计可以量化一个人将这些黑暗扇区喷气机与压倒性QCD背景区分开的能力。这种搜索将从理论进步中受益,以改善预测,并使用在高光度LHC上收集的数据增加统计数据。
We examine the robustness of collider phenomenology predictions for a dark sector scenario with QCD-like properties. Pair production of dark quarks at the LHC can result in a wide variety of signatures, depending on the details of the new physics model. A particularly challenging signal results when prompt production induces a parton shower that yields a high multiplicity of collimated dark hadrons with subsequent decays to Standard Model hadrons. The final states contain jets whose substructure encodes their non-QCD origin. This is a relatively subtle signature of strongly coupled beyond the Standard Model dynamics, and thus it is crucial that analyses incorporate systematic errors to account for the approximations that are being made when modeling the signal. We estimate theoretical uncertainties for a canonical substructure observable designed to be sensitive to the gauge structure of the underlying object, the two-point energy correlator $e_2^{(β)}$, by computing envelopes between resummed analytic distributions and numerical results from Pythia. We explore the separability against the QCD background as the confinement scale, number of colors, number of flavors, and dark quark masses are varied. Additionally, we investigate the uncertainties inherent to modeling dark sector hadronization. Simple estimates are provided that quantify one's ability to distinguish these dark sector jets from the overwhelming QCD background. Such a search would benefit from theory advances to improve the predictions, and the increase in statistics using the data to be collected at the high luminosity LHC.