SciPost Submission Page
Transformer Neural Networks in the Measurement of $t\bar{t}H$ Production in the $H\,{\to}\,b\bar{b}$ Decay Channel with ATLAS
by Chris Scheulen on behalf of the ATLAS Collaboration
Submission summary
| Authors (as registered SciPost users): | Chris Scheulen |
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| Preprint Link: | https://arxiv.org/abs/2412.08387v1 (pdf) |
| Date submitted: | 2024-12-12 16:00 |
| Submitted by: | Scheulen, Chris |
| Submitted to: | SciPost Physics Proceedings |
| Proceedings issue: | The 17th International Workshop on Top Quark Physics (TOP2024) |
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| Academic field: | Physics |
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| Approach: | Experimental |
Abstract
A measurement of Higgs boson production in association with a top quark pair in the bottom anti-bottom Higgs boson decay channel and leptonic final states is presented. The analysis uses $140\,\mathrm{fb}^{-1}$ of $13\,\mathrm{TeV}$ proton proton collision data collected by the ATLAS detector at the Large Hadron Collider. A particular focus is placed on the role played by transformer neural networks in discriminating signal and background processes via multi-class discriminants and in reconstructing the Higgs boson transverse momentum. These powerful multi-variate analysis techniques significantly improve the analysis over a previous measurement using the same dataset.
Current status:
In refereeing