AI 中文总结
研究在CLIC上FCNC顶夸克衰变 \(t\to cH\) 和 \(t\to cS\)，聚焦高能区，通过构建多通道喷注图像并利用CNN分类器增强信号判别，给出了不同衰变模式在特定积分亮度下的预期 \(95\%\) 置信水平上限。
AI 中文摘要
顶夸克与希格斯场有最大的汤川耦合，为电弱对称破缺和标准模型之外的新物理提供独特窗口。本文研究在质心能量 \(\sqrt{s}=1.5\) TeV的紧凑型直线对撞机（CLIC）上，味改变中性流（FCNC）顶夸克衰变 \(t\to cH\) 和 \(t\to cS\)（\(S\) 为轻标量）。分析聚焦于与多数先前研究不同的高能运动学区域，通过构建多通道喷注图像并采用卷积神经网络（CNN）分类器捕捉与FCNC信号相关的喷注子结构模式来增强信号判别。假设积分亮度为 \(4\) \(ab^{-1}\)，得出预期的 \(95\%\) 置信水平上限：\(\mathrm{BR}(t\to cH)\times \mathrm{BR}(H\to b\bar b)<5.27\times10^{-5}\)；对于质量在 \(30\) 到 \(80\) GeV之间的标量单重态，\(\mathrm{BR}(t\to cS)\times \mathrm{BR}(S\to b\bar b)\) 的预期 \(95\%\) 置信水平上限在 \(3.25\times10^{-5}\) 到 \(5.26\times10^{-5}\) 之间。
英文摘要
The top quark, having the largest Yukawa coupling to the Higgs sector, provides a unique window into electroweak symmetry breaking and possible new physics beyond the Standard Model. Searches for rare top-quark processes are thus powerful probes of new physics. In this work, we investigate the flavor-changing neutral-current (FCNC) top-quark decays $t\to cH$ and $t\to cS$, where $S$ denotes a light scalar, at the Compact Linear Collider (CLIC) with a center-of-mass energy of $\sqrt{s}=1.5~\mathrm{TeV}$. Our analysis focuses on a kinematic regime distinct from most previous studies, in which the top quarks are typically highly boosted. To enhance signal discrimination in the boosted regime, we construct multi-channel jet images and employ a convolutional neural network (CNN) classifier to capture jet-substructure patterns relevant to the FCNC signals. Assuming an integrated luminosity of $4~\mathrm{ab}^{-1}$, we obtain the expected $95\%$ C.L. upper limit $\mathrm{BR}(t\to cH)\times \mathrm{BR}(H\to b\bar b)<5.27\times10^{-5}$. For the exotic scalar singlet, expected $95\%$ C.L. upper limits between $3.25\times10^{-5}$ and $5.26\times10^{-5}$ are obtained for $\mathrm{BR}(t\to cS)\times \mathrm{BR}(S\to b\bar b)$, for scalar masses between $30$ and $80~\mathrm{GeV}$.
Comments27 pages, 11 figures, Accepted by PRD
