Higgs self-coupling measurements using deep learning in the b b ¯ b b ¯ $$ b\overline{b}b\overline{b} $$ final state
Abstract Measuring the Higgs trilinear self-coupling λ hhh is experimentally demanding but fundamental for understanding the shape of the Higgs potential. We present a comprehensive analysis strategy for the HL-LHC using di-Higgs events in the four b-quark channel (hh → 4b), extending current method...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2020-12-01
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| Series: | Journal of High Energy Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/JHEP12(2020)115 |
| _version_ | 1819061100805619712 |
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| author | Jacob Amacker William Balunas Lydia Beresford Daniela Bortoletto James Frost Cigdem Issever Jesse Liu James McKee Alessandro Micheli Santiago Paredes Saenz Michael Spannowsky Beojan Stanislaus |
| author_facet | Jacob Amacker William Balunas Lydia Beresford Daniela Bortoletto James Frost Cigdem Issever Jesse Liu James McKee Alessandro Micheli Santiago Paredes Saenz Michael Spannowsky Beojan Stanislaus |
| author_sort | Jacob Amacker |
| collection | DOAJ |
| description | Abstract Measuring the Higgs trilinear self-coupling λ hhh is experimentally demanding but fundamental for understanding the shape of the Higgs potential. We present a comprehensive analysis strategy for the HL-LHC using di-Higgs events in the four b-quark channel (hh → 4b), extending current methods in several directions. We perform deep learning to suppress the formidable multijet background with dedicated optimisation for BSM λ hhh scenarios. We compare the λ hhh constraining power of events using different multiplicities of large radius jets with a two-prong structure that reconstruct boosted h → bb decays. We show that current uncertainties in the SM top Yukawa coupling y t can modify λ hhh constraints by ∼ 20%. For SM y t , we find prospects of −0.8 < λ hhh / λ hhh SM $$ {\lambda}_{hhh}/{\lambda}_{hhh}^{\mathrm{SM}} $$ < 6.6 at 68% CL under simplified assumptions for 3000 fb −1 of HL-LHC data. Our results provide a careful assessment of di-Higgs identification and machine learning techniques for all-hadronic measurements of the Higgs self-coupling and sharpens the requirements for future improvement. |
| first_indexed | 2024-12-21T14:37:31Z |
| format | Article |
| id | doaj.art-7262657c650644a9a72c607badc819e9 |
| institution | Directory Open Access Journal |
| issn | 1029-8479 |
| language | English |
| last_indexed | 2024-12-21T14:37:31Z |
| publishDate | 2020-12-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of High Energy Physics |
| spelling | doaj.art-7262657c650644a9a72c607badc819e92022-12-21T19:00:18ZengSpringerOpenJournal of High Energy Physics1029-84792020-12-0120201215810.1007/JHEP12(2020)115Higgs self-coupling measurements using deep learning in the b b ¯ b b ¯ $$ b\overline{b}b\overline{b} $$ final stateJacob Amacker0William Balunas1Lydia Beresford2Daniela Bortoletto3James Frost4Cigdem Issever5Jesse Liu6James McKee7Alessandro Micheli8Santiago Paredes Saenz9Michael Spannowsky10Beojan Stanislaus11Department of Physics, University of OxfordDepartment of Physics, University of OxfordDepartment of Physics, University of OxfordDepartment of Physics, University of OxfordDepartment of Physics, University of OxfordDepartment of Physics, University of OxfordDepartment of Physics, University of ChicagoDepartment of Physics, University of OxfordDepartment of Physics, University of OxfordDepartment of Physics, University of OxfordInstitute of Particle Physics Phenomenology, Durham UniversityDepartment of Physics, University of OxfordAbstract Measuring the Higgs trilinear self-coupling λ hhh is experimentally demanding but fundamental for understanding the shape of the Higgs potential. We present a comprehensive analysis strategy for the HL-LHC using di-Higgs events in the four b-quark channel (hh → 4b), extending current methods in several directions. We perform deep learning to suppress the formidable multijet background with dedicated optimisation for BSM λ hhh scenarios. We compare the λ hhh constraining power of events using different multiplicities of large radius jets with a two-prong structure that reconstruct boosted h → bb decays. We show that current uncertainties in the SM top Yukawa coupling y t can modify λ hhh constraints by ∼ 20%. For SM y t , we find prospects of −0.8 < λ hhh / λ hhh SM $$ {\lambda}_{hhh}/{\lambda}_{hhh}^{\mathrm{SM}} $$ < 6.6 at 68% CL under simplified assumptions for 3000 fb −1 of HL-LHC data. Our results provide a careful assessment of di-Higgs identification and machine learning techniques for all-hadronic measurements of the Higgs self-coupling and sharpens the requirements for future improvement.https://doi.org/10.1007/JHEP12(2020)115Higgs PhysicsBeyond Standard Model |
| spellingShingle | Jacob Amacker William Balunas Lydia Beresford Daniela Bortoletto James Frost Cigdem Issever Jesse Liu James McKee Alessandro Micheli Santiago Paredes Saenz Michael Spannowsky Beojan Stanislaus Higgs self-coupling measurements using deep learning in the b b ¯ b b ¯ $$ b\overline{b}b\overline{b} $$ final state Journal of High Energy Physics Higgs Physics Beyond Standard Model |
| title | Higgs self-coupling measurements using deep learning in the b b ¯ b b ¯ $$ b\overline{b}b\overline{b} $$ final state |
| title_full | Higgs self-coupling measurements using deep learning in the b b ¯ b b ¯ $$ b\overline{b}b\overline{b} $$ final state |
| title_fullStr | Higgs self-coupling measurements using deep learning in the b b ¯ b b ¯ $$ b\overline{b}b\overline{b} $$ final state |
| title_full_unstemmed | Higgs self-coupling measurements using deep learning in the b b ¯ b b ¯ $$ b\overline{b}b\overline{b} $$ final state |
| title_short | Higgs self-coupling measurements using deep learning in the b b ¯ b b ¯ $$ b\overline{b}b\overline{b} $$ final state |
| title_sort | higgs self coupling measurements using deep learning in the b b ¯ b b ¯ b overline b b overline b final state |
| topic | Higgs Physics Beyond Standard Model |
| url | https://doi.org/10.1007/JHEP12(2020)115 |
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