论文标题
使用$ \ sqrt {s} = 13 $ tev $ pp $ collisions在ATLAS检测器中使用$ \ sqrt {s} = 13 $ \ sqrt {s} = 13
Dijet resonance search with weak supervision using $\sqrt{s}=13$ TeV $pp$ collisions in the ATLAS detector
论文作者
论文摘要
这封信描述了使用机器学习异常检测程序搜索狭ressonant的新物理，该检测过程不依赖信号模拟来开发分析选择。弱监督的学习用于直接对数据进行培训，以增强潜在信号。有针对性的拓扑是Dijet事件，用于机器学习的功能是两个喷气机的质量。最终的分析本质上是三维搜索$ a \ rightarrow bc $，对于$ m_a \ sim \ sim \ Mathcal {o}（\ text {tev}）$，$ m_b，m_c \ sim \ sim \ sim \ sim \ mathcal {o}大型试验因素在两种喷气机质量的扫描中。完整运行2 $ \ sqrt {s} = 13 $ tev $ pp $ collision数据集139 fb $^{ - 1} $由Atlas检测器记录在大型强子撞机上的Atlas检测器用于搜索。没有明显的证据表明，二列二氮的局部过量质谱在1.8和8.2 TEV之间。窄宽度$ a $，$ b $和$ c $颗粒的横截面限制随$ m_a $，$ m_b $和$ m_c $而变化。例如，当$ m_a = 3 $ tev和$ m_b \ gtrsim 200 $ gev时，根据$ m_c $，将1至5 fb之间的生产横截面排除在95％的置信度下。对于某些质量，这些限制的敏感性比包容性的Dijet搜索获得的敏感性高10倍。这些结果与对$ b $和$ c $的专门搜索是标准的型号玻色子的补充。
This Letter describes a search for narrowly resonant new physics using a machine-learning anomaly detection procedure that does not rely on a signal simulations for developing the analysis selection. Weakly supervised learning is used to train classifiers directly on data to enhance potential signals. The targeted topology is dijet events and the features used for machine learning are the masses of the two jets. The resulting analysis is essentially a three-dimensional search $A\rightarrow BC$, for $m_A\sim\mathcal{O}(\text{TeV})$, $m_B,m_C\sim\mathcal{O}(100\text{ GeV})$ and $B,C$ are reconstructed as large-radius jets, without paying a penalty associated with a large trials factor in the scan of the masses of the two jets. The full Run 2 $\sqrt{s}=13$ TeV $pp$ collision data set of 139 fb$^{-1}$ recorded by the ATLAS detector at the Large Hadron Collider is used for the search. There is no significant evidence of a localized excess in the dijet invariant mass spectrum between 1.8 and 8.2 TeV. Cross-section limits for narrow-width $A$, $B$, and $C$ particles vary with $m_A$, $m_B$, and $m_C$. For example, when $m_A=3$ TeV and $m_B\gtrsim 200$ GeV, a production cross section between 1 and 5 fb is excluded at 95% confidence level, depending on $m_C$. For certain masses, these limits are up to 10 times more sensitive than those obtained by the inclusive dijet search. These results are complementary to the dedicated searches for the case that $B$ and $C$ are Standard Model bosons.
