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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2404.07822 |
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| _version_ | 1866915028349747200 |
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| author | Lieberman, Benjamin Dahbi, Salah-Eddine Crivellin, Andreas Stevenson, Finn Tripathi, Nidhi Kumar, Mukesh Mellado, Bruce |
| author_facet | Lieberman, Benjamin Dahbi, Salah-Eddine Crivellin, Andreas Stevenson, Finn Tripathi, Nidhi Kumar, Mukesh Mellado, Bruce |
| contents | To mitigate the model dependencies of searches for new narrow resonances at the Large Hadron Collider (LHC), semi-supervised Neural Networks (NNs) can be used. Unlike fully supervised classifiers these models introduce an additional look-elsewhere effect in the process of optimising thresholds on the response distribution. We perform a frequentist study to quantify this effect, in the form of a trials factor. As an example, we consider simulated $Zγ$ data to perform narrow resonance searches using semi-supervised NN classifiers. The results from this analysis provide substantiation that the look-elsewhere effect induced by the semi-supervised NN is under control. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_07822 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Trials Factor for Semi-Supervised NN Classifiers in Searches for Narrow Resonances at the LHC Lieberman, Benjamin Dahbi, Salah-Eddine Crivellin, Andreas Stevenson, Finn Tripathi, Nidhi Kumar, Mukesh Mellado, Bruce High Energy Physics - Phenomenology To mitigate the model dependencies of searches for new narrow resonances at the Large Hadron Collider (LHC), semi-supervised Neural Networks (NNs) can be used. Unlike fully supervised classifiers these models introduce an additional look-elsewhere effect in the process of optimising thresholds on the response distribution. We perform a frequentist study to quantify this effect, in the form of a trials factor. As an example, we consider simulated $Zγ$ data to perform narrow resonance searches using semi-supervised NN classifiers. The results from this analysis provide substantiation that the look-elsewhere effect induced by the semi-supervised NN is under control. |
| title | Trials Factor for Semi-Supervised NN Classifiers in Searches for Narrow Resonances at the LHC |
| topic | High Energy Physics - Phenomenology |
| url | https://arxiv.org/abs/2404.07822 |