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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.07589 |
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| _version_ | 1866913647580676096 |
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| author | Kvita, Jiří Baroň, Petr Machalová, Monika Přívara, Radek Vodák, Rostislav Tomeček, Jan |
| author_facet | Kvita, Jiří Baroň, Petr Machalová, Monika Přívara, Radek Vodák, Rostislav Tomeček, Jan |
| contents | We study the application of selected ML techniques to the recognition of a substructure of hadronic final states (jets) and their tagging based on their possible origin in current HEP experiments using simulated events and a parameterized detector simulation. The results are then compared with the cut-based method. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_07589 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Machine Learning Based Top Quark and W Jet Tagging to Hadronic Four-Top Final States Induced by SM as well as BSM Processes Kvita, Jiří Baroň, Petr Machalová, Monika Přívara, Radek Vodák, Rostislav Tomeček, Jan High Energy Physics - Phenomenology High Energy Physics - Experiment We study the application of selected ML techniques to the recognition of a substructure of hadronic final states (jets) and their tagging based on their possible origin in current HEP experiments using simulated events and a parameterized detector simulation. The results are then compared with the cut-based method. |
| title | Machine Learning Based Top Quark and W Jet Tagging to Hadronic Four-Top Final States Induced by SM as well as BSM Processes |
| topic | High Energy Physics - Phenomenology High Energy Physics - Experiment |
| url | https://arxiv.org/abs/2501.07589 |