Speaker
Description
In LHC Run 3, a precise treatment of systematic uncertainties in electron identification efficiency and scale factor measurements is important. One of the main sources of uncertainty comes from the estimation and modeling of background contaminations. This work studies the background composition and the data–MC agreement in these measurements using ATLAS Run 3 data and Monte Carlo simulation. The contributions from several background processes are evaluated separately for different electron identification working points, lepton final states and kinematic regions.
The study shows that the ttbar process gives a sizeable contribution in some kinematic regions, especially in the high-pT region and in the dilepton-mass tail. To estimate the effect of the ttbar background on the nominal Z->ee-based electron identification efficiency measurement, muon objects and multilepton selections are implemented in the Tag-and-Probe framework. This makes it possible to define dedicated control regions and constrain the ttbar contribution in the Zmass/Ziso methods. These developments can help improve the precision of electron identification efficiency measurements by treating important background contributions separately and by providing a better understanding of their associated systematic uncertainties.
| 请选择分会 | TeV物理和超出标准模型新物理 |
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