在HL-LHC上解码重型顶夸克亲和共振：从部分子运动学到深度学习信号
Decoding Heavy Top-Philic Resonances at the HL-LHC: From Parton Kinematics to Deep Learning Signatures
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中文总结 AI 辅助
本研究利用有效场论分类和深度神经网络标记器，在高亮度LHC上探测顶夸克亲和重共振，通过四喷注重建实现3.74σ显著性。
中文摘要 AI 辅助
电弱尺度的稳定性强烈激励了对新重共振和顶夸克伙伴态的搜寻。我们研究了在高亮度LHC（$\sqrt{s} = 13.6$ TeV）上，介导矢量型夸克产生的奇异共振的发现潜力，重点关注$pp \to X \to t \bar{t}_p$级联衰变。采用模型无关的有效场论方法，我们按自旋（0和1）和色表示（单态和八重态）对中间媒介粒子$X$进行分类。部分子级运动学表明，关于横动量的归一化微分截面为自旋判别提供了稳健的观测量。为应对高度增强、半分辨强子衰变的实验挑战，我们引入了一种基于包含性四喷注不变质量重建$M(4j)$的切割流策略。由于这种标准方法对系统不确定性仍较敏感，我们实现了一种基于深度神经网络（DNN）的广义BSM标记器。通过利用非线性多喷注关联，DNN实现了从$\mathcal{O}(600)$到$\mathcal{O}(1000)$的稳健背景抑制因子，同时保留了潜在的部分子特征。投影到$3000\text{ fb}^{-1}$的积分亮度，该组合策略对主导的色八重态矢量道产生了$3.74\sigma$的预期统计显著性，确立了强证据潜力，并为未来HL-LHC搜寻提供了稳健的现象学基线。
英文摘要
The stabilization of the electroweak scale strongly motivates the search for new heavy resonances and top-partner states. We investigate the discovery potential of exotic resonances mediating the production of vector-like quarks at the High-Luminosity LHC ($\sqrt{s} = 13.6$ TeV), focusing on the $pp \to X \to t \bar{t}_p$ cascade decay. Using a model-independent Effective Field Theory approach, we classify the intermediate mediator $X$ by its spin (0 and 1) and color (singlet and octet) representations. Parton-level kinematics demonstrate that the normalized differential cross-section with respect to the transverse momentum provides a robust observable for spin discrimination. To address the experimental challenges of highly boosted, semi-resolved hadronic decays, we introduce a cut-flow strategy based on an inclusive four-jet invariant mass reconstruction, $M(4j)$. Because this standard approach remains sensitive to systematic uncertainties, we implement a Generalized BSM Tagger based on Deep Neural Networks (DNNs). By exploiting non-linear multi-jet correlations, the DNN achieves robust background rejection factors ranging from $\mathcal{O}(600)$ to $\mathcal{O}(1000)$ while preserving the underlying partonic signatures. Projecting to an integrated luminosity of $3000\text{ fb}^{-1}$, this combined strategy yields a projected statistical significance of $3.74σ$ for the dominant color-octet vector channel, establishing strong evidence potential and offering a robust phenomenological baseline for future HL-LHC searches.
发表机构
- University of Jijel（吉杰尔大学）
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