Speaker
Description
The production of a top quark in association with a Z and W boson (tWZ) is a rare Standard Model process that provides a sensitive probe of top quark electroweak couplings and constitutes an important background to searches for physics beyond the Standard Model. This contribution presents a study of the sensitivity to tWZ production in the four-lepton (4ℓ) final state with the ATLAS detector. The 4ℓ channel offers a clean experimental signature, but suffers from limited statistics and significant background contributions, particularly from processes such as ttZ.
Using simulated proton–proton collision samples corresponding to LHC Run 2 conditions, a comparison is performed between a traditional analysis strategy based on kinematic observables and a multivariate approach employing a deep neural network trained to distinguish signal from background. The performance of the two approaches is evaluated using the Asimov estimate of the expected signal significance in a statistical-only framework. A substantial improvement in expected sensitivity is observed when using the machine learning–based discriminant, highlighting the power of exploiting multidimensional correlations in complex final states.
The analysis is being extended to incorporate Run 3 data and a comprehensive set of systematic uncertainties, with the goal of establishing a robust measurement of the tWZ process.
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