A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment
A strategy for a general search for new phenomena using data-derived signal regions and its application within the ATLAS experiment
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DOI：
10.1140/epjc/s10052-019-6540-y
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发表时间：
2019-02-06
影响因子：
4.4
通讯作者：
Zwalinski, L.
中科院分区：
文献类型：
--
作者：
Aaboud, M.;Aad, G.;Zwalinski, L.
本文介绍了一种策略，用于一般搜索使用的ATLAS协作，以寻找新的物理学的潜在迹象。事件根据其最终状态被分类为许多事件类。对于每个事件类别，自动搜索算法测试数据是否与对新物理效应敏感的几个分布中的Monte Carlo模拟预期兼容。使用伪实验来量化偏差的显著性。具有显著偏差的数据选择定义了用于具有改进的背景期望的专用随访分析的信号区域。对新数据集上的数据导出信号区域的分析允许在没有大的别处寻找效应的情况下进行统计解释。利用标准模型过程和新物理的基准信号讨论了该方法的灵敏度。作为一个例子，结果显示了2015年在LHC使用ATLAS探测器收集的质量中心能量为13 TeV的3.2fb-1质子-质子碰撞数据，其中分析了700多个事件类别和105多个区域。未发现显著偏离，因此未定义用于随访分析的数据衍生信号区域。
This paper describes a strategy for a general search used by the ATLAS Collaboration to find potential indications of new physics. Events are classified according to their final state into many event classes. For each event class an automated search algorithm tests whether the data are compatible with the Monte Carlo simulated expectation in several distributions sensitive to the effects of new physics. The significance of a deviation is quantified using pseudo-experiments. A data selection with a significant deviation defines a signal region for a dedicated follow-up analysis with an improved background expectation. The analysis of the data-derived signal regions on a new dataset allows a statistical interpretation without the large look-elsewhere effect. The sensitivity of the approach is discussed using Standard Model processes and benchmark signals of new physics. As an example, results are shown for 3.2fb-1 of proton-proton collision data at a centre-of-mass energy of 13TeV collected with the ATLAS detector at the LHC in 2015, in which more than 700 event classes and more than 105 regions have been analysed. No significant deviations are found and consequently no data-derived signal regions for a follow-up analysis have been defined.