Learning to pinpoint effective operators at the LHC: a study of the t t ¯ b b ¯ $$ \mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}} $$ signature
Abstract In the context of the Standard Model effective field theory (SMEFT), we study the LHC sensitivity to four fermion operators involving heavy quarks by employing cross section measurements in the t t ¯ b b ¯ $$ t\overline{t}b\overline{b} $$ final state. Starting from the measurement of total...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2018-11-01
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| Series: | Journal of High Energy Physics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1007/JHEP11(2018)131 |
| _version_ | 1818039944246984704 |
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| author | Jorgen D’Hondt Alberto Mariotti Ken Mimasu Seth Moortgat Cen Zhang |
| author_facet | Jorgen D’Hondt Alberto Mariotti Ken Mimasu Seth Moortgat Cen Zhang |
| author_sort | Jorgen D’Hondt |
| collection | DOAJ |
| description | Abstract In the context of the Standard Model effective field theory (SMEFT), we study the LHC sensitivity to four fermion operators involving heavy quarks by employing cross section measurements in the t t ¯ b b ¯ $$ t\overline{t}b\overline{b} $$ final state. Starting from the measurement of total rates, we progressively exploit kinematical information and machine learning techniques to optimize the projected sensitivity at the end of Run III. Indeed, in final states with high multiplicity containing inter-correlated kinematical information, multi-variate methods provide a robust way of isolating the regions of phase space where the SMEFT contribution is enhanced. We also show that training for multiple output classes allows for the discrimination between operators mediating the production of tops in different helicity states. Our projected sensitivities not only constrain a host of new directions in the SMEFT parameter space but also improve on existing limits demonstrating that, on one hand, t t ¯ b b ¯ $$ t\overline{t}b\overline{b} $$ production is an indispensable component in a future global fit for top quark interactions in the SMEFT, and on the other, multi-class machine learning algorithms can be a valuable tool for interpreting LHC data in this framework. |
| first_indexed | 2024-12-10T08:06:41Z |
| format | Article |
| id | doaj.art-7eda127cce6c48589fd6ec92a9b5e8ac |
| institution | Directory Open Access Journal |
| issn | 1029-8479 |
| language | English |
| last_indexed | 2024-12-10T08:06:41Z |
| publishDate | 2018-11-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of High Energy Physics |
| spelling | doaj.art-7eda127cce6c48589fd6ec92a9b5e8ac2022-12-22T01:56:40ZengSpringerOpenJournal of High Energy Physics1029-84792018-11-0120181113810.1007/JHEP11(2018)131Learning to pinpoint effective operators at the LHC: a study of the t t ¯ b b ¯ $$ \mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}} $$ signatureJorgen D’Hondt0Alberto Mariotti1Ken Mimasu2Seth Moortgat3Cen Zhang4Inter-University Institute for High Energies (IIHE), Vrije Universiteit BrusselInter-University Institute for High Energies (IIHE), Vrije Universiteit BrusselCentre for Cosmology, Particle Physics and Phenomenology (CP3), Université catholique de LouvainInter-University Institute for High Energies (IIHE), Vrije Universiteit BrusselInstitute of High Energy Physics and School of Physical Sciences, University of Chinese Academy of SciencesAbstract In the context of the Standard Model effective field theory (SMEFT), we study the LHC sensitivity to four fermion operators involving heavy quarks by employing cross section measurements in the t t ¯ b b ¯ $$ t\overline{t}b\overline{b} $$ final state. Starting from the measurement of total rates, we progressively exploit kinematical information and machine learning techniques to optimize the projected sensitivity at the end of Run III. Indeed, in final states with high multiplicity containing inter-correlated kinematical information, multi-variate methods provide a robust way of isolating the regions of phase space where the SMEFT contribution is enhanced. We also show that training for multiple output classes allows for the discrimination between operators mediating the production of tops in different helicity states. Our projected sensitivities not only constrain a host of new directions in the SMEFT parameter space but also improve on existing limits demonstrating that, on one hand, t t ¯ b b ¯ $$ t\overline{t}b\overline{b} $$ production is an indispensable component in a future global fit for top quark interactions in the SMEFT, and on the other, multi-class machine learning algorithms can be a valuable tool for interpreting LHC data in this framework.http://link.springer.com/article/10.1007/JHEP11(2018)131Beyond Standard ModelEffective Field Theories |
| spellingShingle | Jorgen D’Hondt Alberto Mariotti Ken Mimasu Seth Moortgat Cen Zhang Learning to pinpoint effective operators at the LHC: a study of the t t ¯ b b ¯ $$ \mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}} $$ signature Journal of High Energy Physics Beyond Standard Model Effective Field Theories |
| title | Learning to pinpoint effective operators at the LHC: a study of the t t ¯ b b ¯ $$ \mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}} $$ signature |
| title_full | Learning to pinpoint effective operators at the LHC: a study of the t t ¯ b b ¯ $$ \mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}} $$ signature |
| title_fullStr | Learning to pinpoint effective operators at the LHC: a study of the t t ¯ b b ¯ $$ \mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}} $$ signature |
| title_full_unstemmed | Learning to pinpoint effective operators at the LHC: a study of the t t ¯ b b ¯ $$ \mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}} $$ signature |
| title_short | Learning to pinpoint effective operators at the LHC: a study of the t t ¯ b b ¯ $$ \mathrm{t}\overline{\mathrm{t}}\mathrm{b}\overline{\mathrm{b}} $$ signature |
| title_sort | learning to pinpoint effective operators at the lhc a study of the t t ¯ b b ¯ mathrm t overline mathrm t mathrm b overline mathrm b signature |
| topic | Beyond Standard Model Effective Field Theories |
| url | http://link.springer.com/article/10.1007/JHEP11(2018)131 |
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