AI 中文总结
该研究比较LHC事件分类器，发现平坦度（flattenicity）触发可减少偏差，适用于双喷注非共面性研究以改进小系统中喷注淬灭搜索。
AI 中文摘要
大型强子对撞机（LHC）最重要的发现之一是在质子-质子（pp）碰撞中观察到与夸克-胶子等离子体（QGP）形成相关的效应。这些观测结果的起源仍然未知。由于许多研究中的事件选择依赖于已知会引入选择偏差的基于多重数的估计量，因此必须探索其他方法来阐明这些现象的起源。本贡献比较了LHC实验中使用的不同事件分类器，旨在评估它们之间的相互兼容性。使用PYTHIA 8模拟的$\sqrt{s}=13$ TeV pp碰撞结果表明，不同的分类器会引入偏差，这些偏差可能掩盖小系统中QGP形成的任何证据。然而，在由平坦度（flattenicity）触发的事件中，这些偏差显著减少或不存在。这一发现激励了将平坦度应用于用于搜索喷注淬灭效应的双喷注非共面性研究。尽管基于多重数的估计量在高多重数事件中与最小偏差pp碰撞相比产生方位角展宽，即使在未包含喷注淬灭的PYTHIA 8中也是如此，但由平坦度触发的事件未显示此类展宽。这表明这一新工具可被LHC实验利用，以改进小系统中的喷注淬灭搜索。
英文摘要
One of the most important discoveries at the LHC is the presence of effects associated with quark-gluon plasma (QGP) formation in proton-proton (pp) collisions. The origin of these observations remains unknown. Since event selection in many studies relies on multiplicity-based estimators known to introduce selection biases, alternative approaches must be explored to elucidate the origin of these phenomena. This contribution presents a comparison of different event classifiers used in LHC experiments, aiming to assess their mutual compatibility. Results for pp collisions at $\sqrt{s}=13$ TeV simulated with PYTHIA 8 indicate that the different classifiers introduce biases that can obscure any evidence of QGP formation in small systems. However, these biases are significantly reduced or absent in events triggered with flattenicity. This finding motivates the application of flattenicity in dijet acoplanarity studies used to search for jet quenching effects. While multiplicity-based estimators produce an azimuthal broadening in high-multiplicity compared with minimum-bias pp collisions, even in PYTHIA 8 that does not incorporate jet quenching, events triggered with flattenicity show no such broadening. This suggests that this novel tool could be exploited by LHC experiments to refine jet-quenching searches in small systems.
