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| Main Author: | |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.21239 |
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Table of Contents:
- Extracting bounds on BSM operators at hadron colliders can be a highly non-trivial task. It can be useful or, depending on the complexity of the event structure, even essential to employ modern analysis techniques in order to measure New-Physics effects. A particular class of such modern methods are Machine-Learning algorithms, which are becoming more and more popular in particle physics. We attempt to gauge their potential in the study of $Vh(\rightarrow b\bar b)$ production processes, focusing on the leptonic decay channels of the vector bosons. Specifically, we employ boosted decision trees using the kinematical information of a given event to discriminate between signal and background. Based on this analysis strategy, we derive bounds on four dimension-6 SMEFT operators and subsequently compare them with the ones obtained from a conventional cut-and-count analysis. We find a mild improvement of $\mathcal{O}(\mathrm{few}\, \%)$ across the different operators.